Using cloud-based data for industrial automation system training

ABSTRACT

A cloud-based performance enhancement service captures and collects data relating to interactions of users with industrial automation systems of multiple industrial customers for storage and analysis on a cloud platform. The service employs a performance enhancement component that analyzes the data to facilitate determining correlations between certain user interactions and favorable performance of an industrial automation system, determining user interactions that are less favorable or unsafe, determining alternative actions that a user can take to achieve a same or similar preferred operational result, generating recommendations relating to the alternative actions, determining or designing components or techniques that can automate a preferred user action, determining improved user assignments in connection with the industrial automation system, and/or generating training modules or presentations based on preferred user actions that can be used to train users to more efficiently interact with an industrial automation system to achieve improved system performance.

RELATED APPLICATIONS

This application claims the priority to U.S. Provisional PatentApplication Ser. No. 61/821,639, filed on May 9, 2013, and entitled“REMOTE SERVICES AND ASSET MANAGEMENT SYSTEMS AND METHODS,” the entiretyof which is incorporated herein by reference.

TECHNICAL FIELD

The subject application relates generally to industrial automation, and,more particularly, to using cloud-based data to facilitate enhancingperformance in connection with an industrial automation system.

BACKGROUND

Industrial automation systems can perform various processes to producedesired products or processed materials. An industrial control systemcan comprise various industrial devices, industrial processes, otherindustrial assets, and network-related assets (e.g., communicationnetwork devices and software).

Industrial controllers and their associated input/output (I/O) devicescan be useful to the operation of modern industrial automation systems.These industrial controllers can interact with field devices on theplant floor to control automated processes relating to such objectivesas product manufacture, material handling, batch processing, supervisorycontrol, and other such applications. Industrial controllers can storeand execute user-defined control programs to effect decision-making inconnection with the controlled process. Such programs can include, butare not limited to, ladder logic, sequential function charts, functionblock diagrams, structured text, or other such programming structures.In general, industrial controllers can read input data from sensors andmetering devices that can provide discreet and telemetric data regardingone or more states of the controlled system, and can generate controloutputs based on these inputs in accordance with the user-definedprogram.

In addition to industrial controllers and their associated I/O devices,some industrial automation systems also can include low-level controlsystems, such as vision systems, barcode marking systems, variablefrequency drives, industrial robots, and the like, which can performlocal control of portions of the industrial process, or which can havetheir own localized control systems.

Operators and other users can interact with industrial automationsystems, for example, to facilitate performing manual operations tofacilitate operation of an industrial automation system and/ormonitoring or managing machines or processes associated with theindustrial automation system. For example, operators and other users caninteract with (e.g., work with, monitor, manage, etc.) industrialdevices, industrial processes, control programs, human machineinterfaces (HMIs), etc., associated with the industrial automationsystem, to facilitate operation of the industrial automation system.Some operators or users can have more experience than other operators orusers, which often can translate into the more experienced operators orusers being better performing operators or users in connection with theindustrial automation system. Also, regardless of the amount ofexperience in industrial automation, some operators or users can performbetter than other operators or users with respect to the industrialautomation system. As a result, an industrial automation system, orportion thereof, typically can operate more efficiently when certainoperators or users (e.g., more experienced or better performingoperators or users) are working with, monitoring, or managing theindustrial automation system, or portion thereof, than when otheroperators or users (e.g., less experienced or lower performing operatorsor users) are working with, monitoring, or managing the industrialautomation system, or portion thereof.

The above-described deficiencies of today's industrial control andbusiness systems are merely intended to provide an overview of some ofthe problems of conventional systems, and are not intended to beexhaustive. Other problems with conventional systems and correspondingbenefits of the various non-limiting embodiments described herein maybecome further apparent upon review of the following description.

SUMMARY

The following presents a simplified summary in order to provide a basicunderstanding of some aspects described herein. This summary is not anextensive overview nor is intended to identify key/critical elements orto delineate the scope of the various aspects described herein. Its solepurpose is to present some concepts in a simplified form as a prelude tothe more detailed description that is presented later.

Various aspects and embodiments of the disclosed subject matter relateto the use of data analysis in a cloud platform to facilitate trainingusers (e.g., operators, technicians, managers, etc.) to more efficientlyinteract with industrial automation systems. A cloud-based trainingservice can employ a performance enhancement component that can captureuser actions with respect to industrial automation systems of multipleindustrial customers across one or more industrial enterprises. Theperformance enhancement component can receive, collect, or obtain datarelating to or representative of the user actions with respect to theindustrial automation systems of multiple industrial customers forstorage and analysis on a cloud platform. The performance enhancementcomponent can analyze the data (e.g., cloud-based data) to generateanalysis results that can be used to facilitate training users to moreefficiently interact with an industrial automation system, improveperformance of an industrial automation system, and/or for otherpurposes, such as those disclosed herein. For instance, based at leastin part on the results of the analysis of the data, the performanceenhancement component can determine correlations between certain userinteractions with an industrial automation system and favorableperformance of the industrial automation system. The performanceenhancement component also can determine user interactions with respectto an industrial automation system that can be less favorable (e.g.,less efficient from a time and/or money standpoint) or unsafe based atleast in part on the data analysis results.

In some implementations, the performance enhancement component candetermine an alternative action(s) that a user can take to achieve asame or similar preferred operational result with respect to theindustrial automation system (e.g., if the user is unable to perform theinitial or primary action(s) for achieving the preferred operationresult) based at least in part on the data analysis results. Theperformance enhancement component can generate a recommendation and/oran alternative action plan relating to the alternative action(s) thatcan be provided to the user to facilitate training the user to achievethe same or similar preferred operational result with respect to theindustrial automation system.

The performance enhancement component also can determine and/or designcomponents, models, or techniques that can be employed to facilitateautomating a preferred user action(s) with respect to an industrialautomation system based at least in part on the data analysis results.For example, if the performance enhancement component determines oridentifies a set of preferred user actions of a user(s) that correlatewith optimal or favorable performance of the industrial automationsystem, the performance enhancement component can facilitate determiningand/or designing one or more components, models, or techniques that canemulate the set of preferred user actions of a user(s). The one or morecomponents, models, or techniques can be employed by or incorporated inthe industrial automation system to automatically perform the set ofpreferred actions that had been performed by the user(s).

In some implementations, based at least in part on the data analysisresults, the performance enhancement component can determine improveduser assignments in connection with the industrial automation system,wherein the improved user assignments can facilitate improvedperformance of the industrial automation system. The performanceenhancement component also can generate training modules or trainingpresentations based at least in part on one or more preferred useractions (e.g., user actions that correlate with favorable performance ofthe industrial automation system). The training modules or trainingpresentations can be used to train users to more efficiently interactwith an industrial automation system to achieve improved systemperformance.

To the accomplishment of the foregoing and related ends, certainillustrative aspects are described herein in connection with thefollowing description and the annexed drawings. These aspects areindicative of various ways which can be practiced, all of which areintended to be covered herein. Other advantages and novel features maybecome apparent from the following detailed description when consideredin conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of an example system (e.g.,performance enhancement system) that can facilitate enhancingperformance (e.g., training users) and performing other operations inconnection with an industrial automation system associated with anindustrial enterprise based on cloud-based data relating to theindustrial enterprise, in accordance with various implementations andembodiments of the disclosed subject matter.

FIG. 2 is a diagram of a high-level overview of an example industrialenterprise that can leverage cloud-based services, including performanceenhancement services, training-related services, data collectionservices, and data storage services, in accordance with various aspectsand embodiments of the disclosed subject matter.

FIG. 3 presents a block diagram of an exemplary system (e.g.,cloud-based, or partially cloud-based, performance enhancement system)according to various implementations and embodiments of the disclosedsubject matter.

FIG. 4 illustrates a diagram of an example system that can facilitateenhancing performance in connection with industrial automation systems,performing training-related functions or operations, or performing otherfunctions or operations, based at least in part collection ofcustomer-specific industrial data by a cloud-based performanceenhancement system, in accordance with various aspects and embodimentsof the disclosed subject matter.

FIG. 5 illustrates a diagram of an example hierarchical relationshipbetween these example data classes.

FIG. 6 depicts a block diagram of an example system that can beconfigured to comprise an industrial device that can act or operate as acloud proxy for other industrial devices of an industrial automationsystem to facilitate migrating industrial data to the cloud platform forclassification and analysis by the performance enhancement system, inaccordance with various aspects and implementations of the disclosedsubject matter.

FIG. 7 illustrates a block diagram of an example system that can employa firewall box that can serve as a cloud proxy for a set of industrialdevices to facilitate migrating industrial data to the cloud platformfor classification and analysis by the performance enhancement system,in accordance with various aspects and implementations of the disclosedsubject matter.

FIG. 8 illustrates a block diagram of an example device model accordingto various aspects and implementations of the disclosed subject matter.

FIG. 9 presents a block diagram of an example system that can facilitatecollection of data from devices and assets associated with respectiveindustrial automation systems for storage in cloud-based data storage,in accordance with various aspects and implementations of the disclosedsubject matter.

FIG. 10 illustrates a block diagram of a cloud-based system that canemploy a performance enhancement system to facilitate enhancingperformance, or performing training-related or other services, inconnection with industrial automation systems, in accordance withvarious aspects and embodiments of the disclosed subject matter.

FIG. 11 illustrates a flow diagram of an example method that canfacilitate training users associated with an industrial automationsystem associated with an industrial enterprise based on cloud-baseddata relating to the industrial enterprise, in accordance with variousimplementations and embodiments of the disclosed subject matter.

FIG. 12 depicts a flow diagram of an example method that can facilitatetraining users associated with an industrial automation systemassociated with an industrial enterprise based on cloud-based datarelating to the industrial enterprise, in accordance with variousimplementations and embodiments of the disclosed subject matter.

FIG. 13 presents a flow diagram of an example method that can facilitateautomating one or more preferred user actions in connection with a worktask associated with an industrial automation system, in accordance withvarious aspects and embodiments of the disclosed subject matter.

FIG. 14 presents a flow diagram of an example method that can facilitatedetermining one or more alternate user actions that a user can performto complete a work task(s) to achieve a same or substantially sameperformance result as when the work task(s) is completed by a user(e.g., another user) by performing one or more user actions (e.g.,preferred user actions), in accordance with various aspects andembodiments of the disclosed subject matter.

FIG. 15 illustrates a flow diagram of another example method that canfacilitate desirably (e.g., acceptably, optimally, etc.) determiningrespective assignments for respective users who perform work tasks inconnection with an industrial automation system, in accordance withvarious aspects and embodiments of the disclosed subject matter.

FIG. 16 is an example computing and/or operating environment.

FIG. 17 is an example computing and/or networking environment.

DETAILED DESCRIPTION

The subject disclosure is now described with reference to the drawings,wherein like reference numerals are used to refer to like elementsthroughout. In the following description, for purposes of explanation,numerous specific details are set forth in order to provide a thoroughunderstanding thereof. It may be evident, however, that the subjectdisclosure can be practiced without these specific details. In otherinstances, well-known structures and devices are shown in block diagramform in order to facilitate a description thereof.

Industrial automation systems can perform various processes to producedesired products or processed materials. An industrial control systemcan comprise various industrial devices, industrial processes, otherindustrial assets, and network-related assets (e.g., communicationnetwork devices and software).

Operators and other users can interact with industrial automationsystems, for example, to facilitate performing manual operations tofacilitate operation of an industrial automation system and/ormonitoring or managing machines or processes associated with theindustrial automation system. For example, operators and other users caninteract with (e.g., work with, monitor, manage, etc.) industrialdevices, industrial processes, control programs, human machineinterfaces (HMIs), etc., associated with the industrial automationsystem, to facilitate operation of the industrial automation system.Some operators or users can have more experience than other operators orusers, which often can translate into the more experienced operators orusers being better performing operators or users in connection with theindustrial automation system. Also, regardless of the amount ofexperience in industrial automation, some operators or users can performbetter than other operators or users with respect to the industrialautomation system. Further, with respect to customers, some operators orusers can be more familiar with or have more knowledge of a particularcustomer's industrial-automation-system configuration than otheroperators or users. For instance, a well-performing operator (e.g.,experienced or skilled operator) can accrue a detailed working knowledgeof how to manage or process for optimal performance given a range ofoperating scenarios (e.g., how to quickly clear a particular fault,which preventative operations will maximize a machine or process uptime,etc.). This can include not only knowledge of the manufacturing processitself, which may be common across multiple customers working in similarindustries, but also knowledge of the idiosyncrasies of a customer'sparticular system configuration (e.g., the particular combination ofmachines, automation devices, and software running the process).

As a result, an industrial automation system, or portion thereof,typically can operate more efficiently when certain operators or users(e.g., more experienced or better performing operators or users,operators or users who are more familiar with a particular customer'sindustrial-automation-system configuration) are working with,monitoring, or managing the industrial automation system, or portionthereof, than when other operators or users (e.g., less experienced orlower performing operators or users, or operators or users who are lessfamiliar with, or are less knowledgeable regarding, a particularcustomer's industrial-automation-system configuration) are working with,monitoring, or managing the industrial automation system, or portionthereof.

To that end, presented are various systems, methods, and techniques ofthe disclosed subject matter that relate to the use of data analysis(e.g., big data analysis) in a cloud platform to facilitate enhancingperformance, and/or performing training-related and other operations, inconnection with industrial automation systems. A cloud-based performanceenhancement service can capture and collect data relating tointeractions of users with industrial automation systems of multipleindustrial customers for storage and analysis on a cloud platform. Thecloud-based performance enhancement service can employ a performanceenhancement component that can analyze the data to generate analysisresults that can be used to facilitate making various determinationsrelating to enhancing performance, and/or training of users, inconnection with an industrial automation system or other determinationsin connection with an industrial automation system, or performing otheractions or operations in connection with an industrial automationsystem, to facilitate improving the performance of the industrialautomation system and the users associated with the industrialautomation system. For instance, based at least in part on the dataanalysis results, the performance enhancement component can facilitatedetermining correlations between certain user interactions and favorableperformance of an industrial automation system, determining userinteractions that are less favorable or unsafe, determining alternativeactions that a user can take to achieve a same or similar preferredoperational result, generating recommendations relating to thealternative actions, determining or designing components or techniquesthat can automate a preferred user action(s), determining improved userassignments in connection with the industrial automation system, and/orgenerating training modules or presentations based at least in part onpreferred user actions that can be used to train users to moreefficiently interact with an industrial automation system to achieveimproved system performance.

As used in this application, the terms “component,” “system,”“platform,” “layer,” “controller,” “terminal,” “station,” “node,”“interface” can refer to a computer-related entity or an entity relatedto, or that is part of, an operational apparatus with one or morespecific functionalities, wherein such entities can be either hardware,a combination of hardware and software, software, or software inexecution. For example, a component can be, but is not limited to being,a process running on a processor, a processor, a hard disk drive,multiple storage drives (of optical or magnetic storage medium)including affixed (e.g., screwed or bolted) or removably affixedsolid-state storage drives; an object; an executable; a thread ofexecution; a computer-executable program, and/or a computer. By way ofillustration, both an application running on a server and the server canbe a component. One or more components can reside within a processand/or thread of execution, and a component can be localized on onecomputer and/or distributed between two or more computers. Also,components as described herein can execute from various computerreadable storage media having various data structures stored thereon.The components may communicate via local and/or remote processes such asin accordance with a signal having one or more data packets (e.g., datafrom one component interacting with another component in a local system,distributed system, and/or across a network such as the Internet withother systems via the signal). As another example, a component can be anapparatus with specific functionality provided by mechanical partsoperated by electric or electronic circuitry which is operated by asoftware or a firmware application executed by a processor, wherein theprocessor can be internal or external to the apparatus and executes atleast a part of the software or firmware application. As yet anotherexample, a component can be an apparatus that provides specificfunctionality through electronic components without mechanical parts,the electronic components can include a processor therein to executesoftware or firmware that provides at least in part the functionality ofthe electronic components. As further yet another example, interface(s)can include input/output (I/O) components as well as associatedprocessor, application, or Application Programming Interface (API)components. While the foregoing examples are directed to aspects of acomponent, the exemplified aspects or features also apply to a system,platform, interface, layer, controller, terminal, and the like.

As used herein, the terms “to infer” and “inference” refer generally tothe process of reasoning about or inferring states of the system,environment, and/or user from a set of observations as captured viaevents and/or data. Inference can be employed to identify a specificcontext or action, or can generate a probability distribution overstates, for example. The inference can be probabilistic—that is, thecomputation of a probability distribution over states of interest basedon a consideration of data and events. Inference can also refer totechniques employed for composing higher-level events from a set ofevents and/or data. Such inference results in the construction of newevents or actions from a set of observed events and/or stored eventdata, whether or not the events are correlated in close temporalproximity, and whether the events and data come from one or severalevent and data sources.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom the context, the phrase “X employs A or B” is intended to mean anyof the natural inclusive permutations. That is, the phrase “X employs Aor B” is satisfied by any of the following instances: X employs A; Xemploys B; or X employs both A and B. In addition, the articles “a” and“an” as used in this application and the appended claims shouldgenerally be construed to mean “one or more” unless specified otherwiseor clear from the context to be directed to a singular form.

Furthermore, the term “set” as employed herein excludes the empty set;e.g., the set with no elements therein. Thus, a “set” in the subjectdisclosure includes one or more elements or entities. As anillustration, a set of controllers includes one or more controllers; aset of data resources includes one or more data resources; etc.Likewise, the term “group” as utilized herein refers to a collection ofone or more entities; e.g., a group of nodes refers to one or morenodes.

Various aspects or features will be presented in terms of systems thatmay include a number of devices, components, modules, and the like. Itis to be understood and appreciated that the various systems may includeadditional devices, components, modules, etc. and/or may not include allof the devices, components, modules etc. discussed in connection withthe figures. A combination of these approaches also can be used.

FIG. 1 illustrates a block diagram of an example system 100 (e.g.,performance enhancement system) that can facilitate enhancingperformance, training users, and/or performing other operations inconnection with an industrial automation system associated with anindustrial enterprise based on cloud-based data relating to theindustrial enterprise, in accordance with various implementations andembodiments of the disclosed subject matter. The system 100 can leveragethe broad range of customer-related data that can be captured and storedin the cloud platform to facilitate enhancing performance, trainingusers, and/or performing other operations in connection with theindustrial automation system, wherein the customer-related data cancharacterize the assets and automation process of the customer'sindustrial automation system. The system 100 also can capture datarelating to the workflow, interactions, behavior, and habits of usersand store such data in the cloud platform, wherein such data also can beused to facilitate enhancing performance or training users in connectionwith working with the industrial automation system.

The system 100 can comprise a collection component 102 (e.g., datacollection component) that can be associated with an industrialautomation system 104 associated with an industrial enterprise. Theindustrial automation system 104 can comprise one or more industrialdevices 106, industrial processes 108, or other industrial assets 110that can be distributed throughout an industrial facility(ies) inaccordance with a desired industrial-automation-system configuration.The industrial automation system 104 can perform industrial processes orother actions to facilitate producing desired products, processedmaterials, etc., as an output.

The industrial automation system 104 also can include a networkcomponent 112 that can be associated with (e.g., interfaced with,communicatively connected to) the various industrial devices 106,processes 108, and/or other assets 110 of the industrial automationsystem 104 to facilitate communication of information (e.g., command orcontrol information, status information, production information, etc.)between the various industrial devices 106, processes 108, and/or otherassets 110 via the network component 112. The network component 112 canbe associated with (e.g., interfaced with, communicatively connected to)the collection component 102 to facilitate the communication of databetween the industrial automation system 104 and the collectioncomponent 102.

The collection component 102 can monitor or track the operation of theindustrial automation system 104 and users associated with theindustrial automation system 104 (e.g., operators, technicians,managers, engineers, etc., interacting or working with the industrialautomation system 104). The collection component 102 can receive,obtain, detect, capture, or collect data relating to the operation ofthe industrial automation system 104, the users associated with theindustrial automation system 104, and the network component 112. Thecollection component also can receive, obtain, detect, capture, orcollect data from other sources, such as extrinsic sources.

The collection component 102 can receive, obtain, detect, capture, orcollect data relating to the work or interactions of users with theindustrial automation system 104 and the network component 112. Forexample, the collection component 102 can receive and/or capture datarelating to the respective work or interactions of respective users withthe industrial automation system 104, including the respective work orinteractions of respective users with the various industrial devices106, processes 108, HMIs, control programs, other assets 110, thenetwork component 112, etc., associated with the industrial automationsystem 104. The collection component 102 can comprise or be associatedwith various sensor components (not shown in FIG. 1) that can facilitatesensing, detecting, obtaining, or capturing data relating to the work orinteractions of users with the industrial automation system 104 and thenetwork component 112, the operation of the industrial automation system104, and the operation of the network component 112. The sensorcomponents can comprise, for example, video sensor components that canbe distributed across the industrial automation system 104 and can senseor capture visual data, audio sensor components that can be distributedacross the industrial automation system 104 and can sense or captureaudio data, motion sensor components that can be distributed across theindustrial automation system 104 and can sense or capture motion data,operational sensor components that can be distributed across theindustrial automation system 104 and can sense or capture variousoperational aspects or parameters (e.g., status, temperature, quantity,quality, etc.) relating to the industrial automation system 104,location sensor components that can sense the respective locations ofrespective users (e.g., based at least in part on determining therespective locations of their respective mobile communication devices ortags (e.g., radio-frequency identification (RFID) tags), etc. Forexample, the collection component 102, e.g., via the various sensorcomponents, can facilitate capturing user actions and/or behavior withrespect to the various portions (e.g., various industrial devices 106,processes 108, HMIs, control programs, other assets 110, the networkcomponent 112, etc.) of the industrial automation system 104.

The collection component 102 also, e.g., via the various sensorcomponents, can receive, obtain, detect, capture, or collect datarelating to the industrial devices 106 (e.g., operation or status of theindustrial devices, properties or characteristics of the industrialdevices, maintenance records of the industrial devices, configurationsof the industrial devices, etc.), industrial processes 108 (e.g.,operation or status of the industrial processes, properties orcharacteristics of the industrial processes, maintenance recordsassociated with the industrial processes, configurations of theindustrial processes, etc.), and the other industrial assets 110 (e.g.,operation or status of the industrial assets, properties orcharacteristics of the industrial assets, maintenance records associatedwith the industrial assets, configurations of the industrial assets,etc.). The collection component 102 also can receive or collect datarelating to operation of the components of the network component 112(e.g., operation or status of the network devices or assets,communication conditions associated with a communication channel, totalbandwidth of a communication channel, available bandwidth of acommunication channel, properties or characteristics of the networkdevices or assets, maintenance records associated with the networkdevices or assets, configurations of the network devices or assets,etc.).

The system 100 also can comprise a data store 114 that can be associatedwith (e.g., interfaced with, communicatively connected to) thecollection component 102. The collection component 102 can provide(e.g., communicate, write, etc.) the data relating to the userinteractions with the industrial automation system 104, the operation ofthe industrial automation system 104, and the operation of the networkcomponent 112 to the data store 114 for storage in the data store 114.

The system 100 further can include a performance enhancement component116 that can facilitate performing various tasks and functions relatingto enhancing performance of users and/or the industrial automationsystem 104, training users associated with the industrial automationsystem 104, or performing other tasks and functions. In accordance withvarious implementations, the performance enhancement component 116 cancomprise the collection component 102, or a portion thereof, and/or thedata store 114, or a portion thereof, or can be associated with (e.g.,interfaced with, communicatively connected to) the collection component102 and/or the data store 114 to facilitate obtaining data associatedwith the users, the industrial automation system 104, and networkcomponent 112, or data obtained from other sources (e.g., extrinsicsources), wherein the data (e.g., big data or cloud data) can beanalyzed by the performance enhancement component 116 to facilitateperforming the various tasks and functions relating to enhancingperformance and/or training users in connection with the industrialautomation system 104 or performing other tasks and functions.

The performance enhancement component 116 can determine or identifycorrelations between certain user interactions or behaviors inconnection with operation of an industrial automation system 104 andfavorable performance of the industrial automation system 104, inaccordance with a set of defined performance criteria. The set ofdefined performance criteria can facilitate defining what is consideredfavorable performance of an industrial automation system 104 ordetermining whether performance of an industrial automation system 104is favorable. The set of defined performance criteria, includingcriteria relating to favorable performance of an industrial automationsystem 104, can be or relate to, for example, whether a golden batch(e.g., a defined optimal or ideal production batch or operation run) hasbeen achieved in operation of an industrial automation system 104,whether a desired (e.g., an optimal, or a substantially or acceptablyclose to optimal) condition or result has been achieved in operation ofthe industrial automation system 104, whether a lack or substantial lackof poor user actions has been observed or determined in connection withthe operation of the industrial automation system 104, whether a lack orsubstantial lack of breakdowns or repairs have been observed ordetermined in connection with the operation of the industrial automationsystem 104, whether a desired amount of energy usage (e.g., desirably,optimally, or acceptably small amount of energy usage) has been achievedin connection with the operation of the industrial automation system104, whether a lowest or acceptably low cost of operation of (e.g.,lowest or acceptably low cost per unit produced by) the industrialautomation system 104 has been achieved, or other desired criteria(e.g., criteria relating to favorable performance of an industrialautomation system, as desired or specified by a customer).

In accordance with various implementations, in accordance with the setof defined performance criteria, the performance enhancement component116 can determine or identify preferred user actions in relation to(e.g., in connection with) the industrial automation system 104 (e.g.,user actions that result in more favorable performance of the industrialautomation system 104), determine or identify poor or unsafe userpractices in relation to the industrial automation system 104 (e.g.,user actions that result in less favorable performance of the industrialautomation system 104 or are unsafe), facilitate training users toperform their tasks more efficiently with respect to the industrialautomation system 104 (e.g., based at least in part on the preferreduser actions), facilitate automating preferred user actions, and/orperforming other tasks or functions, as more fully disclosed herein. Thedisclosed subject matter, including the various aspects andimplementations regarding the performance enhancement component 116,collection component 102, and data store 114, can be employed tofacilitate the set up and deployment of an industrial automationsystem(s), improvement of an industrial automation system(s),performance analysis relating to operation of the of an industrialautomation system(s), cost analysis (e.g., production cost analysis)relating to an industrial automation system(s), training of users (e.g.,operators, technicians, managers, engineers, maintenance personnel,etc.) associated with an industrial automation system(s), etc.

In some implementations, the performance enhancement component 116,collection component 102, and/or the data store 114 can be located in acloud platform that can be interfaced with the industrial automationsystem 104. In accordance with various other implementations, one ormore of the performance enhancement component 116, collection component102, and/or the data store 114 can be located at the plant or originalequipment manufacturer (OEM) level associated with the industrialautomation system 104, or can be located in a different platform orlevel.

To facilitate performing performance-enhancement-related functions oroperations (e.g., determining preferred user actions in relation to theindustrial automation system 104, determining poor or unsafe userpractices in relation to the industrial automation system 104,facilitating training users to perform their tasks more efficiently withrespect to the industrial automation system 104 (e.g., based at least inpart on the preferred user actions), facilitating automating preferreduser actions, etc.), the performance enhancement component 116 canaccess the data store 114 (e.g., cloud-based data store) to obtain a setof data relating to the operation of the industrial automation system104 and/or another industrial automation system (e.g., another systemcomprising an industrial device(s), process(es), and/or asset(s) thatcan be the same or similar to an industrial device(s) 106, process(es)108, and/or asset(s) 110 of the industrial automation system 104), theinteraction or behavior of users in relation to the industrialautomation system 104 and/or another industrial automation system (e.g.,another system comprising an industrial device(s), process(es), and/orasset(s) that can be the same or similar to an industrial device(s) 106,process(es) 108, and/or asset(s) 110 of the industrial automation system104), the operation of the network component 112, and/or the interactionor behavior of users in relation to the network component 112. The setof data can comprise information relating to, for example, the work,interactions, or behavior of users in relation to the industrialautomation system 104 and the network component 112; the respectiveoperations, responses, properties, characteristics, functions,configurations, etc., of respective industrial devices 106, industrialprocesses 108, other industrial assets 110, or network-related devicesof the network component 112; or the configuration of industrial devices106, industrial processes, or other assets in relation to each other.

For example, with regard to work, interactions, or behavior of users inrelation to the industrial automation system 104 or network component112, the set of data can include information relating to affirmativeactions taken by users in connection with the industrial automationsystem 104 or network component 112, active or passive responses ofusers in connection with the industrial automation system 104 or networkcomponent 112 (e.g., response of user to an operation or response of theindustrial automation system 104 or network component 112, response ofuser to an alarm or notification associated with the industrialautomation system 104 or network component 112, etc.), shift-specific oruser-specific behavior or interaction of users (e.g., operators,managers, technicians, etc.) with the industrial automation system 104,work schedules or assignments of users, maintenance schedules forrespective portions of the industrial automation system 104 or networkcomponent 112, production or process flows of the industrial automationsystem 104 at particular times or in connection with particular projectsor users, and/or other aspects or features of the industrial automationsystem 104. For instance, the performance enhancement component 116 canmonitor keystrokes of users, mouse movements made by users, HMI screennavigations of users, information displayed on an HMI screen (e.g., viaHMI screen captures), manual control panel interactions (e.g., sequenceand timing of pushbutton and/or switch operations), observed usagepatterns of users, observed operator locations in relation to theindustrial automation system 104, etc. The performance enhancementcomponent 116 can associate (e.g., link, map, marry, etc.) the capturedhuman activity data with particular user identifiers, for example, usingexplicit login information (e.g., username, password, etc.) forrespective users, by detecting (e.g., automatically detecting) theuser's mobile communication device (e.g., mobile phone, electronic pador tablet, laptop computer, etc., via a communication device identifier(e.g., media access control (MAC) address)) or other identifier or tag(e.g., radio-frequency identification (RFID) tag) associated with theuser near the location of activity (e.g., determine who is interactingwith an industrial device, process, or asset based at least in part onproximity of the user's mobile communication device to the industrialdevice, process, or asset), or by detecting (e.g., automaticallydetecting) biometric information (e.g., information relating tofingerprints, facial recognition, eye or iris recognition, etc.) of auser near the location of activity, etc. In some scenarios, monitoringof a user's mobile communication device (e.g., personal communicationdevice) by the performance enhancement component 116 can be contingenton approval from both the customer (associated with the industrialfacility) and/or the user.

The performance enhancement component 116 can utilize authenticationtechniques and/or can leverage the authentication procedures associatedwith the industrial automation system 104 to facilitate identifyingusers and their relationship to or interactions with the industrialautomation system 104. If a user (e.g., an authorized operator) is usinga device associated with the industrial automation system 104, and thedevice is handed over to a different user (e.g., portable device isphysically passed from one user to another user, or the other user takesover operation of the device), the performance enhancement component 116can detect the new user who is operating the device based at least inpart on authentication information (e.g., username, password, biometricinformation, etc.) associated with the new user and/or by detecting thelocation of the new user in relation to the device based at least inpart on the new user's communication device (e.g., the location of thecommunication device via the communication device identifier) and/or IDtag (e.g., RFID tag) of the user. In some implementations, theperformance enhancement component 116 can facilitate controlling accessto devices, processes, or assets associated with the industrialautomation system 104 by a user based at least in part on authenticationof the user. For example, the performance enhancement component 116 canfacilitate granting access to devices, processes, or assets associatedwith the industrial automation system 104 to users who present validauthentication information to the performance enhancement component 116or industrial automation system 104, and denying access to devices,processes, or assets associated with the industrial automation system104 to users who do not present valid authentication information to theperformance enhancement component 116 or industrial automation system104.

The performance enhancement component 116 also can facilitate scoping ortailoring the data collection, including the collection and use ofidentification information or authentication information associated witha user, in a manner that can add value to facilitate the performance offunctions and operations by the performance enhancement component 116without impeding production by the users or the industrial automationsystem 104, or violating safety procedures. For example, in somesituations, fingerprint-based or retina-based authentication informationmay not be appropriate in areas of the industrial enterprise thatrequire gloves or goggles to be worn by users. As another example, inother situations, monitoring of a communication device (e.g., mobilecommunication device) of a user may not be possible or suitable forareas of the industrial enterprise where constant or reliable networkcommunication (e.g., wireless network communication) is not available.With regard to such situations, the performance enhancement component116 can facilitate determining the location of a user, determining adevice or process being operated by the user, performingtraining-related functions or operations, etc., through other means(e.g., username or password provided by the user in connection with adevice, process, or location; work assignment information for respectiveusers; etc.). In some implementations, the performance enhancementcomponent 116 or another component can notify a user if the monitoringof the user's location may increase the user's risk of exposure toelectromagnetic forces (EMFs).

With further regard to the set of data, as an example of properties orcharacteristics of data in the set of data, the properties orcharacteristics for industrial devices 106 or industrial processes 108can comprise mechanical or process properties or characteristicsassociated with industrial devices or processes (e.g., mechanicallatency, process cycle times, operating schedules, etc., associated withindustrial devices). The properties or characteristics fornetwork-related devices can comprise communication properties orcharacteristics (e.g., wireless and/or wireline communicationfunctionality, type(s) of network or communication protocol(s), networkor communication specifications, total bandwidth, etc.) of therespective network-related devices, etc.

The set of data also can comprise information relating to, for example,the configuration of the network-related devices in relation to eachother, or the configuration of network-related devices in relation tothe industrial devices 106, industrial processes 108, and/or otherindustrial assets 110; software, firmware, and/or operating systemutilized by the industrial automation system 104 (e.g., type(s),version(s), revision(s), configuration(s), etc., of the software,firmware, and/or operating system); functional and communicativerelationships between industrial devices 106, industrial processes 108,industrial assets 110, network-related devices of the network component112, etc. (e.g., communication connections or conditions betweenindustrial devices, types of connections between industrial devices,communication connections between industrial devices and network-relateddevices, etc.).

The performance enhancement component 116 can analyze (e.g., perform“big data” analysis on) the set of data relating to the industrialautomation system 104 and/or the other industrial automation system, andcan generate analysis results based at least in part on the analysis ofthe set of data, to facilitate enhancing performance of the industrialautomation system 104 or users associated therewith, performing varioususer-training-related functions or operations, or performing otherfunctions or operations (e.g., automating preferred user actions), inconnection with the industrial automation system 104. The performanceenhancement component 116 also can tailor the data analysis on the setof data, and even can tailor the set of data, based at least in part onthe performance-enhancement-related functions or operations,user-training-related functions or operations, or other functions oroperations. For instance, in connection with a first function (e.g.,determining preferred user actions in relation to the industrialautomation system 104), the performance enhancement component 116 cantailor a first set of data and tailor a first data analysis on thatfirst set of data to facilitate efficiently performing the firstfunction; and in connection with a second function (e.g., automatingpreferred user actions in relation to the industrial automation system104), the performance enhancement component 116 can tailor the secondset of data and tailor the second data analysis on the second set ofdata to facilitate efficiently performing the second function. Forinstance, with regard to the first function, the performance enhancementcomponent 116 can tailor the first set of data retrieved from the datastore 114 to obtain data that is determined to be relevant to theperforming the first function. The performance enhancement component 116also can tailor the first data analysis on the first set of data toefficiently obtain a desired result (e.g., accurately determining oridentifying a preferred user action(s)) from performing the firstfunction (e.g., determining preferred user actions in relation to theindustrial automation system 104). The performance enhancement component116 can tailor the data and analysis in connection with performing thesecond function in a similar manner that corresponds to the secondfunction.

Based at least in part on the results of the data analysis (e.g.,analysis of the human behavior data and other relevant data), theperformance enhancement component 116 can determine or identifycorrelations between certain user actions (e.g., certain human action orbehavior sequences) and favorable performance by the industrialautomation system 104. This can thereby facilitate determining oridentifying preferred or optimal user behavior that facilitatespreferred or optimal performance of the industrial automation system104. In this way, the performance enhancement component 116 can analyzehuman behavior patterns to facilitate determining how operators are tointeract with particular industrial devices or machines, industrialprocesses, or industrial assets to achieve more favorable performance bythe industrial automation system 104.

For instance, based at least in part on the analysis results, theperformance enhancement component 116 can determine or identifypreferred user actions in relation to (e.g., in connection with) theindustrial automation system 104 (e.g., user actions that result in morefavorable performance of the industrial automation system 104), inaccordance with a set of defined performance criteria. For example,based at least in part on the analysis results, the performanceenhancement component 116 can determine or identify that theinteraction(s) or behavior(s) of a first user in connection with anoperation(s) or event(s) associated with the industrial automationsystem 104 resulted in a more favorable response or performance of theindustrial automation system 104 than a response or performance of theindustrial automation system 104 that resulted from other interactionsor behaviors of other users in connection with a same or similaroperation(s) or event(s) associated with the industrial automationsystem 104. The performance enhancement component 116 can determine oridentify the interaction(s) or behavior(s) of the first user as being apreferred user action(s) (e.g., an action or a sequence of actions) thatis to be implemented in connection with the operation(s) or event(s)associated with the industrial automation system 104, in accordance withthe set of defined performance criteria.

In some implementations, the performance enhancement component 116 canfurther analyze the interaction(s) or behavior(s) of the first user inconnection with the operation(s) or event(s) associated with theindustrial automation system 104 to facilitate determining whether theaction(s) of the first user can be improved, enhanced, or modified tofacilitate gaining an even more favorable response or performance of theindustrial automation system 104 than the favorable response orperformance of the industrial automation system 104 that resulted fromthe interaction(s) or behavior(s) of the first user in connection withthe operation(s) or event(s) associated with the industrial automationsystem 104, in accordance with the set of defined performance criteria.If the performance enhancement component 116 determines that theaction(s) of the first user can be improved, enhanced, or modified tofacilitate gaining an even more favorable response or performance of theindustrial automation system 104, the performance enhancement component116 can determine or identify the interaction(s) or behavior(s) of thefirst user, as further improved, enhanced, or modified, as being apreferred user action(s) (e.g., an action or a sequence of actions) thatis to be implemented in connection with the operation(s) or event(s)associated with the industrial automation system 104, in accordance withthe set of defined performance criteria.

For example, based at least in part on the analysis results, theperformance enhancement component 116 can determine that, in a sequenceof four actions performed by the first user in connection with theoperation(s) or event(s) associated with the industrial automationsystem 104, the first action, second action, and fourth action wereoptimal or at least substantially optimal, but the third action wassubstantially sub-optimal (e.g., failed to satisfy a defined thresholdperformance parameter or parameter range), in accordance with the set ofdefined performance criteria. The performance enhancement component 116can determine a different or modified action that a user can perform,instead of performing the third action in the way the first userperformed it, based at least in part on the data analysis results,wherein the different or modified action can satisfy the applicabledefined threshold performance parameter or parameter range, inaccordance with the set of defined performance criteria.

The performance enhancement component 116 can generate a trainingpresentation or training module illustrating or presenting the preferreduser action(s) (e.g., as originally performed by the first user, or asimproved, enhanced, or modified by the performance enhancement component116) and/or comprising a set of instructions that can facilitatetraining users to perform the preferred user action(s) in connectionwith the operation(s) or event(s) associated with the industrialautomation system 104. The performance enhancement component 116 canstore the training presentation or training module, or a portionthereof, in the data store 114, and/or can provide the trainingpresentation or training module for use (e.g., presentation) in trainingusers. The training presentation can be or comprise, for example, avideo (e.g., an animated video), a visual illustration, an audiopresentation, a training model, an interactive training simulation,printed materials (e.g., written instructions, training manual or guide,etc.), a searchable training or troubleshooting database (e.g.,knowledgebase), a poster, a placard, and/or another suitable trainingpresentations, presenting or illustrating the preferred user action(s)(or alternate user action(s), as disclosed herein). The trainingpresentation or training module can be used to facilitate training users(e.g., new or inexperienced user, poor performing user) to perform theirwork tasks (e.g., work duties, work assignments, etc.) more efficientlywhen working with the industrial automation system 104 (e.g., based atleast in part on the preferred user action(s)).

The performance enhancement component 116 also can determine or identifypoor or unsafe user practices, and the users who are engaging in thepoor or unsafe practices, in relation to the industrial automationsystem 104 (e.g., user actions that result in less favorable performanceof the industrial automation system 104 or are unsafe), based at leastin part on the data analysis results, in accordance with the set ofdefined performance criteria. For instance, the performance enhancementcomponent 116 can determine or identify actions or behaviors of users inconnection with an operation(s) or event(s) associated with theindustrial automation system 104 that result in a relatively poorperformance or response by the industrial automation system 104, are atleast potentially unsafe as potentially being harmful to a user(s) or tothe industrial automation system 104, and/or that have resulted in harmto a user(s) or the industrial automation system 104, in accordance withthe set of defined performance criteria. The performance enhancementcomponent 116 also can determine or identify the differences in useractions, habits, workflows, etc., between highly productive users andmoderately or poorly productive users to facilitate determiningpreferred user actions, alternate user actions, or unproductive orunsafe user actions.

The performance enhancement component 116 can generate a trainingpresentation or training module illustrating or presenting the poor orunsafe user action(s) and/or comprising a set of instructions,guidelines, or recommendations that can facilitate training instructingusers to not perform the poor or unsafe user action(s) in connectionwith the operation(s) or event(s) associated with the industrialautomation system 104 to facilitate mitigating poor work performancehabits of under-performing users. The performance enhancement component116 can store this training presentation or training module, or aportion thereof, in the data store 114, and/or can provide this trainingpresentation or training module for use (e.g., presentation) in trainingusers. This training presentation or training module can be employed tofacilitate training users (e.g., new or inexperienced user, poorperforming user) to perform their tasks more efficiently and/or safelywith respect to the industrial automation system 104.

The performance enhancement component 116 can facilitate determining oneor more alternate user actions that a user can perform to complete awork task to achieve a same or substantially same performance result aswhen the work task is completed by another user through performing oneor more user actions (e.g., preferred user actions). For example, insome instances, a first user is able to perform one or more user actions(e.g., preferred user actions) to complete a work task in connectionwith the industrial automation system that produces a favorableperformance or response by the industrial automation system, whereas asecond user may not be able to perform the one or more user actions thatthe first user was able to perform when performing the work task. Forinstance, the second user may have physical limitations or otherlimitations (e.g., mental limitations, skill limitations, etc.) that canmake it difficult, if not impossible, for the second user to perform theone or more user actions the way the first user was able to performthem. Based at least in part on the data analysis results, theperformance enhancement component 116 can determine one or morealternate user actions that can be performed by the second user tocomplete the work task to achieve a same or substantially sameperformance result as when the work task is performed by the first userthrough performing one or more user actions (e.g., preferred useractions).

The performance enhancement component 116 also can facilitate automatingpreferred user actions in connection with the operation(s) or event(s)associated with the industrial automation system 104 so that theindustrial automation system 104 can automatically perform the preferreduser actions in connection with the operation(s) or event(s) associatedwith the industrial automation system 104 without a user having toperform the preferred user actions. To facilitate automating a preferreduser action(s), the performance enhancement component 116 can determineand/or design components, models, techniques, or algorithms that, whenimplemented by the industrial automation system 104, can facilitatehaving the industrial automation system 104 perform (e.g., automaticallyperform) the preferred user action(s), based at least in part on thedata analysis results. For example, if the performance enhancementcomponent 116 determines or identifies a set of preferred user actionsof a user(s) that correlate with optimal or favorable performance of theindustrial automation system 104, the performance enhancement component116 can facilitate determining and/or designing one or more components,models, techniques, or algorithms that can emulate or reproduceperforming the set of preferred user actions of a user(s). Thecomponents or models can comprise hardware and/or software. With regardto software-related components or models, the performance enhancementcomponent 116 can facilitate determining, designing, and/or generatingcode (e.g., machine or computer executable code) that can facilitateemulating the performance of the preferred user actions by the user. Theperformance enhancement component 116 or another component canfacilitate employing or incorporating the one or more components,models, or techniques by or in the industrial automation system 104 tofacilitate enabling the industrial automation system 104 toautomatically perform the set of preferred actions that previously hadbeen performed by the user(s).

In some implementations, based at least in part on the data analysisresults, the performance enhancement component 116 also can determineimproved user assignments in connection with the industrial automationsystem 104, wherein the improved user assignments can facilitateimproved performance of the industrial automation system 104. Forexample, based at least in part on the data analysis results, theperformance enhancement component 116 can determine or identify that afirst user performs better than a second user in connection with a firstportion (e.g., a first industrial process or first subset of industrialdevices) of the industrial automation system 104 resulting in morefavorable performance when the first user is interacting or working withthe first portion of the industrial automation system 104. Theperformance enhancement component 116 also can determine or identifythat the first user and second user perform comparably (e.g., the sameor substantially the same) in connection with a second portion (e.g., asecond industrial process or second subset of industrial devices) of theindustrial automation system 104. With this knowledge that the firstuser performs better than the second user with regard to the firstportion and the first user and second user perform comparably withregard to the second portion, in accordance with the set of definedperformance criteria, the performance enhancement component 116 candetermine that the first user is to be assigned to work with the firstportion of the industrial automation system 104 and the second user isto be assigned to work with the second portion of the industrialautomation system 104 for a particular work shift because such workassignments will produce a more favorable or improved performance by theindustrial automation system 104 than if the second user was assigned towork with the first portion and the first user was assigned to work withthe second portion. The performance enhancement component 116 cangenerate work assignments that assign the first user to work with thefirst portion of the industrial automation system 104 and assign thesecond user to work with the second portion of the industrial automationsystem 104 for that particular work shift. The performance enhancementcomponent 116 can store the work assignments in the data store 114and/or present the work assignments via a desired interface (e.g.,display screen, printer, etc.).

In some implementations, to facilitate designing, developing, orgenerating training presentations or training modules, or determining,developing, designing, or generating components, models, or techniquesthat can facilitate automating one or more preferred user actions, theperformance enhancement component 116 can facilitate simulating oremulating the industrial automation system 104 and its constituentindustrial devices, processes, and other assets, and/or simulating oremulating preferred user actions, or simulating or emulating components,models, or techniques that can reproduce or perform the one or morepreferred users actions. Based at least in part on the results of theanalysis of the set of data, the performance enhancement component 116can simulate or emulate (e.g., determine and/or generate a simulation oran emulation for) the industrial automation system 104, includingdetermining respectively simulating or emulating the respectiveindustrial devices 106, industrial processes 108, other assets 110, andnetwork-related devices of the network component 112, simulating oremulating the interrelationships (e.g., system configuration,connections, etc.) between the respective industrial devices 106,industrial processes 108, other industrial assets 110, andnetwork-related devices of the network component 112, and/or simulatingor emulating the properties, characteristics, functions, etc., of therespective devices, processes, and/or assets of the industrialautomation system 104, etc. Based at least in part on the results of theanalysis of the set of data, the performance enhancement component 116also can simulate or emulate (e.g., determine and/or generate asimulation or an emulation for) one or more components, models, ortechniques that can facilitate automating one or more preferred useractions to facilitate developing or generating one or more components,models, or techniques that can be incorporated in or used by theindustrial automation system 104 to facilitate automating performance ofthe one or more preferred actions by the industrial automation system104 (e.g., instead of a user performing the one or more preferredactions) and enabling the industrial automation system 104 to performmore favorably and efficiently (e.g., based at least in part on theautomating of the one or more preferred user actions), in accordancewith the set of defined performance criteria.

As disclosed herein, the system 100 (e.g., training system 100), or aportion thereof, can be located in a cloud platform. To provide ageneral context for the cloud-based system and services describedherein, FIG. 2 illustrates a block diagram of a high-level overview ofan example industrial enterprise 200 that can leverage cloud-basedservices, including training-related services, data collection services,and data storage services, in accordance with various aspects andembodiments of the disclosed subject matter. The industrial enterprise200 can comprise one or more industrial facilities, such as industrialfacility₁ 204 ₁ up through industrial facility_(N) 204 _(N), whereineach industrial facilitate can include a number of industrial devices inuse. For example, industrial facility₁ 204 ₁ can comprise industrialdevice₁ 208 ₁ up through industrial device_(N) 208 _(N), and industrialfacility_(N) 204 _(N) can comprise industrial device₁ 210 ₁ up throughindustrial device_(N) 210 _(N). The industrial devices (e.g., 208 ₁, 208_(N), 210 ₁, 210 _(N), etc.) can make up one or more automation systemsthat can operate within the respective industrial facilities (e.g.,industrial facility₁ 204 ₁ up through industrial facility_(N) 204 _(N)).Exemplary industrial automation systems can include, but are not limitedto, batch control systems (e.g., mixing systems), continuous controlsystems (e.g., proportional-integral-derivative (PID) control systems),or discrete control systems. Industrial devices (e.g., 208 ₁, 208 _(N),210 ₁, 210 _(N), etc.) can include such industrial devices as industrialcontrollers (e.g., programmable logic controllers or other types ofprogrammable automation controllers); field devices such as sensors andmeters; motor drives; HMIs; industrial robots, barcode markers, andreaders; vision system devices (e.g., vision cameras); smart welders; orother types of industrial devices.

Exemplary industrial automation systems can include one or moreindustrial controllers that can facilitate monitoring and controlling oftheir respective industrial processes. The industrial controllers canexchange data with the field devices using native hardwired input/output(I/O) or via a plant network, such as Ethernet/Internet Protocol (IP),Data Highway Plus, ControlNet, Devicenet, or the like. A givenindustrial controller typically can receive any combination of digitalor analog signals from the field devices that can indicate a currentstate of the industrial devices and/or their associated industrialprocesses (e.g., temperature, position, part presence or absence, fluidlevel, etc.), and can execute a user-defined control program that canperform automated decision-making for the controlled industrialprocesses based on the received signals. The industrial controller canoutput appropriate digital and/or analog control signaling to the fielddevices in accordance with the decisions made by the control program.These outputs can include device actuation signals, temperature orposition control signals, operational commands to a machining ormaterial handling robot, mixer control signals, motion control signals,and the like. The control program can comprise any suitable type of codethat can be used to process input signals read into the controller andto control output signals generated by the industrial controller,including, but not limited to, ladder logic, sequential function charts,function block diagrams, structured text, or other such platforms.

Although the exemplary overview illustrated in FIG. 2 depicts theindustrial devices (e.g., 208 ₁, 208 _(N), 210 ₁, 210 _(N)) as residingin fixed-location industrial facilities (e.g., industrial facility₁ 204₁ up through industrial facility_(N) 204 _(N), respectively), in someimplementations, the industrial devices (e.g., 208 ₁, 208 _(N), 210 ₁,and/or 210 _(N)) also can be part of a mobile control and/or monitoringapplication, such as a system contained in a truck or other servicevehicle.

One or more users, such as user₁ 212 ₁, user₂ 212 ₂, up through user_(N)212 _(N), can be employed to perform various work tasks in connectionwith the industrial facility₁ 204 ₁, and one or more users, such asuser₁ 214 ₁, user₂ 214 ₂, up through user_(N) 214 _(N), can be employedto perform various work tasks in connection with the industrialfacility_(N) 204 _(N). The users of the industrial facility₁ 204 ₁ canhave communication devices, such as communication device₁ 216 ₁,communication device₂ 216 ₂, up through communication device_(N) 216_(N), and the users of the industrial facility_(N) 204 _(N) can havecommunication devices, such as communication device₁ 218 ₁,communication device₂ 218 ₂, up through communication device_(N) 218_(N). The respective communications devices can be, for example, amobile phone (e.g., cellular phone, smart phone, etc.), a computer(e.g., laptop computer), an electronic pad or tablet, an RFID tag, orother type of communication or computing device (e.g., device withcommunication and/or computing capabilities). The respective users canuse the respective communication devices to facilitate performing theirrespective work tasks or providing information regarding the respectivelocations of the respective users and/or respective communicationdevices. The respective users also can use the respective communicationsdevices for other uses (e.g., personal use).

In some implementations, one or more sensor components, such as sensorcomponent₁ 220 ₁, sensor component₂ 220 ₂, up through sensorcomponent_(N) 220 _(N), can be distributed throughout industrialfacility₁ 204 ₁, and one or more sensor components, such as sensorcomponent₁ 222 ₁, sensor component₂ 222 ₂, up through sensorcomponent_(N) 222 _(N), can be distributed throughout industrialfacility_(N) 204 _(N). The respective sensor components can facilitatesensing, detecting, obtaining, or capturing data relating to the work orinteractions of users (e.g., user₁ 212 ₁, user₂ 212 ₂, user_(N) 212_(N), user₁ 214 ₁, user₂ 214 ₂, user_(N) 214 _(N)) in connection withthe industrial automation systems and network components of therespective industrial facilities (e.g., industrial facility₁ 204 ₁,industrial facility_(N) 204 _(N)), and the operation of the respectiveindustrial automation systems and respective network components. Thesensor components can comprise, for example, video sensor componentsthat can be distributed throughout the respective industrial facilities(e.g., industrial facility₁ 204 ₁, industrial facility_(N) 204 _(N)) andcan sense or capture visual data, audio sensor components that can bedistributed throughout the respective industrial facilities (e.g.,industrial facility₁ 204 ₁, industrial facility_(N) 204 _(N)) and cansense or capture audio data, motion sensor components that can bedistributed throughout the respective industrial facilities (e.g.,industrial facility₁ 204 ₁, industrial facility_(N) 204 _(N)) and cansense or capture motion data, operational sensor components that can bedistributed throughout the respective industrial facilities (e.g.,industrial facility₁ 204 ₁, industrial facility_(N) 204 _(N)) and cansense or capture various operational aspects or parameters (e.g.,status, temperature, quantity, quality, etc.) relating to the respectiveindustrial automation systems or respective network components, locationsensor components that can sense the respective locations of respectiveusers (e.g., based at least in part on determining the respectivelocations of their respective mobile communication devices or tags(e.g., RFID tags), etc. In certain implementations, a sensorcomponent(s) can be within an industrial device or asset.

The collection component (e.g., 102), e.g., via the various sensorcomponents, can facilitate capturing user actions and/or behavior withrespect to the various portions (e.g., various industrial devices,industrial processes, HMIs, control programs, other industrial assets,the network components, etc.) of or associated with the respectiveindustrial automation systems. The collection component also, e.g., viathe various sensor components, can receive, obtain, detect, capture, orcollect data relating to the respective industrial devices (e.g.,operation or status of the industrial devices, properties orcharacteristics of the industrial devices, maintenance records of theindustrial devices, configurations of the industrial devices, etc.),respective industrial processes (e.g., operation or status of theindustrial processes, properties or characteristics of the industrialprocesses, maintenance records associated with the industrial processes,configurations of the industrial processes, etc.), and the otherrespective industrial assets (e.g., operation or status of theindustrial assets, properties or characteristics of the industrialassets, maintenance records associated with the industrial assets,configurations of the industrial assets, etc.). The collection componentalso can receive or collect data relating to operation of the componentsof the network component (e.g., operation or status of the networkdevices or assets, communication conditions associated with acommunication channel, total bandwidth of a communication channel,available bandwidth of a communication channel, properties orcharacteristics of the network devices or assets, maintenance recordsassociated with the network devices or assets, configurations of thenetwork devices or assets, etc.).

According to one or more embodiments of the disclosed subject matter,the industrial devices (e.g., 208 ₁, 208 ₂, 208 _(N), 210 ₁, 210 ₂, 210_(N), etc.), the communication devices (e.g., 216 ₁, 216 ₂, 216 _(N),218 ₁, 218 ₂, 218 _(N), etc.), and/or the sensor components (e.g., 220₁, 220 ₂, 220 _(N), 222 ₁, 222 ₂, 222 _(N), etc.) can be coupled to(e.g., communicatively connected to) a cloud platform 202 to facilitateleveraging cloud-based applications and services (e.g., trainingservices, data collection services, data storage services, simulationgeneration services, etc.) associated with the cloud platform 202. Thatis, the industrial devices (e.g., 208 ₁, 208 ₂, 208 _(N), 210 ₁, 210 ₂,210 _(N), etc.), the communication devices (e.g., 216 ₁, 216 ₂, 216_(N), 218 ₁, 218 ₂, 218 _(N), etc.), and/or the sensor components (e.g.,220 ₁, 220 ₂, 220 _(N), 222 ₁, 222 ₂, 222 _(N), etc.) can be configuredto discover and/or interact with (e.g., communicate with) cloud-basedcomputing services 224 that can be hosted by the cloud platform 202. Thecloud platform 202 can be any infrastructure that can allow cloudservices 224 (e.g., cloud-based computing services, shared computingservices) to be accessed and utilized by cloud-capable devices. Thecloud platform 202 can be a public cloud that can be accessible via apublic network, such as the Internet, by devices having public networkconnectivity (e.g., Internet connectivity) and appropriateauthorizations to utilize the cloud services 224. In some scenarios, thecloud platform 202 can be provided by a cloud provider as aplatform-as-a-service (PaaS), and the cloud services 224 can reside andexecute on the cloud platform 202 as a cloud-based service. In some suchconfigurations, access to the cloud platform 202 and associated cloudservices 224 can be provided to customers as a subscription service byan owner of the cloud services 224. Additionally and/or alternatively,the cloud platform 202 can be a private cloud that can be operatedinternally by the industrial enterprise 200 or an associated enterpriseassociated with a third-party entity. An exemplary private cloudplatform can comprise a set of servers that can host the cloud services224 and can reside on a private network (e.g., an intranet, a corporatenetwork, etc.) that can be protected by a firewall.

The cloud services 224 can include, but are not limited to, datacollection, data storage, data analysis, control applications (e.g.,applications that can generate and deliver control instructions toindustrial devices (e.g., 208 ₁, 208 _(N), 210 ₁, 210 _(N), etc.) basedon analysis of real-time or near real-time system data or otherfactors), remote monitoring and support, determining preferred oralternate user actions, generating training presentations or modules,automating user actions, enhancing work assignments, or otherapplications or services (e.g.,) relating to industrial automation(e.g., simulating or emulating industrial automation systems; simulatingor emulating devices, components, or techniques that facilitateautomating user actions). If the cloud platform 202 is a web-basedcloud, industrial devices (e.g., 208 ₁, 208 _(N), 210 ₁, 210 _(N), etc.)at the respective industrial facilities 204 can interact with cloudservices 224 via the public network (e.g., the Internet). In anexemplary configuration, the industrial devices (e.g., 208 ₁, 208 ₂, 208_(N), 210 ₁, 210 ₂, 210 _(N), etc.), the communication devices (e.g.,216 ₁, 216 ₂, 216 _(N), 218 ₁, 218 ₂, 218 _(N), etc.), and/or the sensorcomponents (e.g., 220 ₁, 220 ₂, 220 _(N), 222 ₁, 222 ₂, 222 _(N), etc.)can access the cloud services 224 through separate cloud gateways (e.g.,cloud gateway 206 ₁ up through cloud gateway 206 _(N)) at the respectiveindustrial facilities (e.g., industrial facility₁ 204 ₁ up throughindustrial facility_(N) 204 _(N), respectively), wherein the industrialdevices the industrial devices (e.g., 208 ₁, 208 ₂, 208 _(N), 210 ₁, 210₂, 210 _(N), etc.), the communication devices (e.g., 216 ₁, 216 ₂, 216_(N), 218 ₁, 218 ₂, 218 _(N), etc.), and/or the sensor components (e.g.,220 ₁, 220 ₂, 220 _(N), 222 ₁, 222 ₂, 222 _(N), etc.) can connect to therespective cloud gateways (e.g., cloud gateway 206 ₁ up through cloudgateway 206 _(N)) through a physical (e.g., wireline) or wireless localarea network or radio link. In another exemplary configuration, theindustrial devices (e.g., 208 ₁, 208 ₂, 208 _(N), 210 ₁, 210 ₂, 210_(N), etc.), the communication devices (e.g., 216 ₁, 216 ₂, 216 _(N),218 ₁, 218 ₂, 218 _(N), etc.), and/or the sensor components (e.g., 220₁, 220 ₂, 220 _(N), 222 ₁, 222 ₂, 222 _(N), etc.) can access the cloudplatform 202 directly using an integrated cloud gateway service. Cloudgateways (e.g., cloud gateway 206 ₁ up through cloud gateway 206 _(N))also can comprise an integrated component of a network infrastructuredevice, such as a firewall box, router, or switch.

Providing industrial devices and other devices or components with cloudcapability via the cloud gateways (e.g., cloud gateway 206 ₁ up throughcloud gateway 206 _(N)) can offer a number of advantages particular toindustrial automation. For instance, cloud-based storage (e.g.,cloud-based data store) offered by the cloud platform 202 can be easilyscaled to accommodate the large quantities of data that can be generateddaily by an industrial enterprise. Further, multiple industrialfacilities (e.g., industrial facility₁ 204 ₁ up through industrialfacility_(N) 204 _(N)) at different geographical locations can migrate(e.g., communicate) their respective industrial automation data to thecloud platform 202 (e.g., via the collection component) for aggregation,collation, collective big data analysis, and enterprise-level reportingwithout the need to establish a private network between the respectiveindustrial facilities. The industrial devices (e.g., 208 ₁, 208 ₂, 208_(N), 210 ₁, 210 ₂, 210 _(N), etc.), the communication devices (e.g.,216 ₁, 216 ₂, 216 _(N), 218 ₁, 218 ₂, 218 _(N), etc.), and/or the sensorcomponents (e.g., 220 ₁, 220 ₂, 220 _(N), 222 ₁, 222 ₂, 222 _(N), etc.)having smart configuration capability can be configured to automaticallydetect and communicate with the cloud platform 202 upon installation atany facility, which can thereby simplify integration with existingcloud-based data storage, analysis, or reporting applications used bythe industrial enterprise 200. In other exemplary applications,cloud-based training-related applications (e.g., utilized by thetraining system comprising the performance enhancement component) canaccess the data relating to an industrial automation system(s) stored inthe cloud-based data store, can determine preferred user actions inconnection with performing a work task, can determine alternate useractions that can be performed instead of other user actions (e.g.,preferred user actions), can generate training presentations or modules,can facilitate determining or designing components, devices, techniques,or algorithms that can facilitate automating user actions (e.g.,automating preferred user actions), can enhance or optimize workassignments, and/or can generate a simulation model that can simulatethe operation of the industrial automation system(s), simulatecomponents, devices, techniques, or algorithms that can facilitateautomating user actions, or simulate operation of the industrialautomation system(s) based at least in part on simulating performance ofusers at respective work assignments (e.g., to facilitate determiningenhanced or optimized work assignments), as more fully disclosed herein.These industrial cloud-computing applications and services are onlyintended to be exemplary, and the systems and methods described hereinare not limited to these particular applications or services. As theseexamples demonstrate, the cloud platform 202, working with cloudgateways (e.g., cloud gateway 206 ₁ up through cloud gateway 206 _(N)),can allow builders of industrial applications to provide scalablesolutions as a service, removing the burden of maintenance, upgrading,and backup of the underlying infrastructure and framework.

FIG. 3 presents a block diagram of an exemplary system 300 (e.g.,cloud-based, or partially cloud-based, training system) according tovarious implementations and embodiments of the disclosed subject matter.Aspects of the systems, apparatuses, or processes explained in thisdisclosure can constitute machine-executable components embodied withinmachine(s), e.g., embodied in one or more computer-readable mediums (ormedia) associated with one or more machines. Such components, whenexecuted by one or more machines, e.g., computer(s), computingdevice(s), automation device(s), virtual machine(s), etc., can cause themachine(s) to perform the operations described.

The system 300 can comprise a communicator component 302 that can beused to communicate (e.g., transmit, receive) information between thesystem 300 and other components (e.g., industrial devices, other typesof industrial assets that have communication functionality,communication devices, sensor components, other devices withcommunication functionality that are associated with industrialenterprises, cloud gateways, etc.). The information can include, forexample, data relating to industrial automation systems, data relatingto specifications, properties, or characteristics of industrial devicesor other industrial assets, user-related data, customer-related data,work-order-related data relating to work orders that will or may behandled by an industrial automation system, etc.

The system 300 can comprise an aggregator component 304 that canaggregate data received (e.g., obtained, collected, detected, etc.) fromvarious entities (e.g., industrial devices, industrial assets, cloudgateways, users (e.g., operators, managers, technicians, etc.),communication devices, other devices with communication functionalitythat are associated with industrial enterprises, processor component(s),user interface(s), data store(s), customers, etc.). The aggregatorcomponent 304 can correlate respective items of data based at least inpart on type of data, source of the data, time or date the data wasgenerated or received, type of device or asset, identifier associatedwith a device or asset, user (e.g., operator, manager, technician, etc.)associated with the data, customer associated with the data, industrialautomation system associated with the data, industrial enterpriseassociated with the system, etc., to facilitate processing of the data(e.g., analyzing of the data, determining preferred or alternate useractions for performing a work task, generating training presentations,enhancing or optimizing work assignments, etc.).

The system 300 also can include a monitor component 306 that can monitordevice data, process data, asset data, system data, user-related data,customer-related data, and/or other data in connection with theindustrial automation systems. For instance, the monitor component 306can monitor information (e.g., signals, device or process statuses,network communication of information, process flows, updates,modifications, etc.) associated with industrial automation systems,industrial enterprises, and/or systems or devices of customersassociated with the industrial enterprises to facilitate detectinginformation associated with industrial automation systems that can beused to facilitate performing training-related functions or operations,or other functions or operations, associated with industrial automationsystems. The monitor component 306 can be associated with sensorcomponents, meters, HMIs, user communication devices (e.g., mobilephone, RFID tag, etc., of a user (e.g., operator, manager, technician,etc.) associated with an industrial automation system), communicationmonitoring components, or other components associated with industrialautomation systems, industrial enterprises, and/or systems or devices ofthe customers to facilitate the monitoring of the industrial automationsystems, industrial enterprises, and/or systems or devices of thecustomers.

The system 300 can comprise a detector component 308 that can detectdesired information associated with industrial automation systems thatcan facilitate performing training-related functions or operations, orother functions or operations, associated with industrial automationsystems, in accordance with the set of defined performance criteria. Forinstance, the detector component 308 can detect desired device data,process data, asset data, system data, user-related data, and/orcustomer-related data in connection with the industrial automationsystems that can facilitate performing training-related functions oroperations, or other functions or operations.

The system 300 also can include a collection component 310 that canreceive, collect, or obtain data (e.g., desired device data, processdata, asset data, system data, user-related data, customer-related data,extrinsic data from extrinsic sources) to facilitate performingtraining-related functions or operations, or other functions oroperations, as more fully disclosed herein. The data collected by thecollection component 310 can be stored in the data store 322, and/or canbe made available to other components (e.g., analyzer component 316,performance enhancement component 318, etc.) to facilitate performingtraining-related functions or operations, or performing other functionsor operations, using the data.

The system 300 can comprise an interface component 312 that can beemployed to facilitate interfacing the system 300 with industrialautomation systems and their constituent components (e.g., industrialdevices or assets, network-related devices or assets, etc.) orprocesses, systems or devices associated with customers, systems ordevices associated with device manufacturers, etc. For instance, theinterface component 312 can be configured to receive industrial data(e.g., device data, process data, asset data, system data, configurationdata, status data, process variable data, etc.) sent by one or morecloud-capable industrial devices, cloud gateways, or other sources ofindustrial data. The interface component 312 also can be configured toreceive network-related data (e.g., data relating to communicationconditions, network-status data, data identifying network-relateddevices, etc.) communicated by one or more network-related devices ofthe network component of an industrial automation system.

The interface component 312 further can be configured to exchange datawith one or more client or customer devices via a communicationconnection (e.g., an Internet connection, a wireless communicationconnection, etc.). For example, the interface component 312 can receivecustomer profile data, requests for firmware upgrades, customer serviceselections, information relating to work orders for products, customerpreferences or requirements with regard to a work order, or other suchinformation from a client device (e.g., an Internet-capable clientdevice, such as a phone, a computer, an electronic tablet or pad, orother suitable Internet-capable device). The interface component 312also can deliver upgrade notifications, firmware upgrades, reports ornotifications regarding the evaluation of and determinations regardingproposed modifications to an industrial automation system, notificationsof impending device failures, identification of asset or systeminefficiencies, configuration recommendations, or other such data to theclient device.

The training system 300 also can contain a controller component 314 cancontrol operations relating to processing data, determining preferredusers actions, determining an alternate user action(s) to be performedinstead of a preferred user action, generating training presentations,automating user actions for automatic performance of such actions by anindustrial automation system, determining enhanced or optimized workassignments for users, generating simulation models that can simulate oremulate industrial automation systems, and/or other operations. Thecontroller component 314 can facilitate controlling operations beingperformed by various components of the system 300, controlling data flowbetween various components of the system 300, controlling data flowbetween the system 300 and other components or systems associated withthe system 300, etc.

The analyzer component 316 can analyze data (e.g., device data, processdata, asset data, system data, user-related data, customer-related data,and/or other data) to facilitate determining preferred user actionsassociated with performing a work task in connection with an industrialautomation system, determining an alternate user action(s) that can beperformed in place of a preferred user action to facilitate performing awork task, generating a training presentation or module, determining ordesigning a component(s), a process(es), a technique(s), or analgorithm(s) that can facilitate automating user actions (e.g.,automatically performing actions that were preferred user actions),determining enhanced or optimized work assignments for users associatedwith an industrial automation system, generating simulation models ofindustrial automation systems to facilitate performing training-relatedfunctions or operations or other functions or operations, etc. Theanalyzer component 316 can parse data to facilitate identifying datathat is relevant to performing an operation (e.g., determining apreferred user action, generating a training presentation, etc.) by thesystem 300. Based at least in part on the analysis of the data, theanalyzer component 316 can generate analysis results that can beprovided to another component (e.g., performance enhancement component318, processor component 320, etc.) to facilitate the performance ofvarious operations by the system 300.

The system 300 also can comprise a performance enhancement component 318that can perform various functions, operations, or tasks to facilitatetraining users associated with an industrial automation system toperform work tasks associated with the industrial automation system moreefficiently and safely to facilitate achieving more favorableperformance of the industrial automation system. The performanceenhancement component 318 can determine one or more preferred useractions for completing a work task to achieve favorable performance ofthe industrial automation system. The performance enhancement component318 also can determine an alternate user action(s) that can be performedin place of a preferred user action to facilitate performing a worktask, wherein the alternate user action(s) can still achieve a same orsubstantially same performance result for the industrial automationsystem as that associated with the preferred user action. Theperformance enhancement component 318 also can generate a trainingpresentation or module (e.g., based at least in part on a preferred useraction(s) or alternate user action(s)) that can be used to facilitatetraining users to perform work tasks more efficiently or safely. Theperformance enhancement component 318 further can determine or design acomponent(s), process(es), technique(s), or algorithm(s) that canfacilitate automating user actions (e.g., automatically performingactions that were preferred user actions). The performance enhancementcomponent 318 also can determine enhanced or optimized work assignmentsfor users associated with an industrial automation system. In someimplementations, the performance enhancement component 318 can generatesimulation models of an industrial automation system and/orcomponent(s), process(es), technique(s), or algorithm(s) that canfacilitate automating user actions to facilitate performingtraining-related functions or operations, determining or designingcomponent(s), process(es), technique(s), or algorithm(s) that canfacilitate automating user actions, or performing other functions oroperations. For example, the performance enhancement component 318 cancomprise a simulation generator component or an emulator component thatrespectively can facilitate simulating or emulating industrialautomation systems, industrial devices, industrial processes, industrialassets, network components, network-related devices, user actions,interrelationships between various entities (e.g., connections betweenvarious devices), etc.

The system 300 also can comprise a processor component 320 that canoperate in conjunction with the other components (e.g., communicatorcomponent 302, aggregator component 304, monitor component 306, etc.) tofacilitate performing the various functions and operations of the system300. The processor component 320 can employ one or more processors(e.g., central processing units (CPUs), graphical processing units(GPUs), field-programmable gate arrays (FPGAs), etc.), microprocessors,or controllers that can process data, such as industrial data (e.g.,device data, process data, asset data, system data, etc.) associatedwith industrial control systems, user-related data, customer or clientrelated data, data relating to parameters associated with the system 300and associated components, etc., to facilitate determining preferreduser actions associated with performing a work task in connection withan industrial automation system, determining an alternate user action(s)that can be performed in place of a preferred user action to facilitateperforming a work task, generating a training presentation or module,determining or designing a component(s), process(es), technique(s), oralgorithm(s) that can facilitate automating user actions (e.g.,automatically performing actions that were preferred user actions),determining enhanced or optimized work assignments for users associatedwith an industrial automation system, generating simulation models ofindustrial automation systems to facilitate performing training-relatedfunctions or operations or other functions or operations, etc.; and cancontrol data flow between the system 300 and other components associatedwith the system 300.

In yet another aspect, the system 300 can contain a data store 322 thatcan store data structures (e.g., user data, metadata); code structure(s)(e.g., modules, objects, classes, procedures), commands, orinstructions; industrial data or other data associated with industrialautomation systems or industrial enterprises; user-related data;customer or client related information; data relating to generation ofsimulation models of industrial automation systems; parameter data;algorithms (e.g., algorithm(s) relating to performing training-relatedoperations, automating user actions, simulating or emulating industrialdevices, industrial processes, industrial assets, network-relateddevices, interrelationships between such devices, processes, or assets,etc.); a set of defined operation criteria; and so on. In an aspect, theprocessor component 320 can be functionally coupled (e.g., through amemory bus) to the data store 322 in order to store and retrieve datadesired to operate and/or confer functionality, at least in part, to thecommunicator component 302, aggregator component 304, monitor component306, etc., of the system 300 and/or substantially any other operationalaspects of the system 300. It is to be appreciated and understood thatthe various components of the system 300 can communicate data,instructions, or signals between each other and/or between othercomponents associated with the system 300 as desired to carry outoperations of the system 300. It is to be further appreciated andunderstood that respective components (e.g., communicator component 302,aggregator component 304, monitor component 306, etc.) of the system 300each can be a stand-alone unit, can be included within the system 300(as depicted), can be incorporated within another component of thesystem 300 (e.g., within the performance enhancement component 318) or acomponent separate from the system 300, and/or virtually any suitablecombination thereof, as desired.

In accordance with various embodiments, one or more of the variouscomponents of the system 300 (e.g., communicator component 302,aggregator component 304, monitor component 306, etc.) can beelectrically and/or communicatively coupled to one another to performone or more of the functions of the system 300. In some implementations,one or more components of the system 300 (e.g., communicator component302, aggregator component 304, monitor component 306, . . . ,performance enhancement component 318) can comprise softwareinstructions that can be stored in the data store 322 and executed bythe processor component 320. The system 300 also can interact with otherhardware and/or software components not depicted in FIG. 3. For example,the processor component 320 can interact with one or more external userinterface devices, such as a keyboard, a mouse, a display monitor, atouchscreen, or other such interface devices.

FIG. 4 illustrates a diagram of an example system 400 that canfacilitate performing training-related functions or operations, or otherfunctions or operations, based at least in part collection ofcustomer-specific industrial data by a cloud-based training system, inaccordance with various aspects and embodiments of the disclosed subjectmatter. The system 400 can include a training system 402 that canexecute as a cloud-based service on a cloud platform (e.g., cloudplatform 202 of FIG. 2), and can collect data from multiple industrialautomation systems, such as industrial automation system₁ 404 ₁,industrial automation system₂ 404 ₂, and/or (up through) industrialautomation system_(N) 404 _(N). The industrial automation systems (e.g.,404 ₁, 404 ₂, 404 _(N)) can comprise different industrial automationsystems within a given facility and/or different industrial facilitiesat diverse geographical locations. Industrial automation systems (e.g.,404 ₁, 404 ₂, 404 _(N)) also can correspond to different businessentities (e.g., different industrial enterprises or customers), whereinthe training system 402 can collect and maintain a distinct customerdata store 406 for each customer or business entity.

The training system 402 can organize manufacturing data collected fromthe industrial automation systems (e.g., 404 ₁, 404 ₂, 404 _(N))according to various classes. In the illustrated example, manufacturingdata can be classified according to device data 408, process data 410,asset data 412, and system data 414.

Referring briefly to FIG. 5, FIG. 5 illustrates a diagram of an examplehierarchical relationship 500 between these example data classes. Agiven plant or supply chain 502 can comprise one or more industrialautomation systems 504. The industrial automation systems 504 canrepresent the production lines or productions areas within a given plantfacility or across multiple facilities of a supply chain. Eachindustrial automation system 504 can comprise a number of assets 506that can represent the machines and equipment that make up theindustrial automation system (e.g., the various stages of a productionline). In general, each asset 506 can comprise one or more industrialdevices 508, which can include, for example, the programmablecontrollers, motor drives, HMIs, sensors, meters, etc. comprising theasset 506. The various data classes depicted in FIGS. 4 and 5 are onlyintended to be exemplary, and it is to be appreciated that anyorganization of industrial data classes maintained by the trainingsystem 402 is within the scope of one or more embodiments of thedisclosed subject matter.

Returning again to FIG. 4, the training system 402 can collect andmaintain data from the various devices and assets that make up theindustrial automation systems 504 and can classify the data according tothe aforementioned classes for the purposes of facilitating analyzingthe data, determining preferred user actions in connection withperforming work tasks associated with the industrial automation systems(e.g., 404 ₁, 404 ₂, 404 _(N)), determining an alternate user action(s)that can replace a preferred user action, generating trainingpresentations or modules, automating user actions for automaticperformance of such actions by an industrial automation system,determining enhanced work assignments for users, generating simulationmodels of the industrial automation systems (e.g., 404 ₁, 404 ₂, 404_(N)), and/or performing other operations by the training system 402.Device data 408 can comprise device-level information relating to theidentity, configuration, and status of the respective devices comprisingthe industrial automation systems (e.g., 404 ₁, 404 ₂, 404 _(N)),including but not limited to device identifiers, device statuses,current firmware versions, health and diagnostic data, devicedocumentation, identification and relationship of neighboring devicesthat interact with the device, etc.

The process data 410 can comprise information relating to one or moreprocesses or other automation operations carried out by the devices;e.g., device-level and process-level faults and alarms, process variablevalues (speeds, temperatures, pressures, etc.), and the like.

The asset data 412 can comprise information generated, collected,determined, or inferred based on data that can be aggregated fromvarious (e.g., multiple) industrial devices over time, which can yieldhigher asset-level views of the industrial automation systems (e.g., 404₁, 404 ₂, 404 _(N)). Example asset data 412 can include performanceindicators (KPIs) for the respective assets, asset-level processvariables, faults, alarms, etc. Since the asset data 412 can yield arelatively longer term view of asset characteristics relative to thedevice and process data, the training system 402 can leverage the assetdata 412 to facilitate identifying operational patterns and correlationsunique to each asset, among other types of analysis, and this canfacilitate simulation or emulation of the respective assets andgeneration of a simulation model of an industrial control system basedon the simulation or emulation of the respective assets associated withthe industrial control system.

The system data 414 can comprise collected, determined, or inferredinformation that can be generated based on data that can be aggregatedfrom various (e.g., multiple) assets over time. The system data 414 cancharacterize system behavior within a large system of assets, yielding asystem-level view of each of the industrial automation systems (e.g.,404 ₁, 404 ₂, 404 _(N)). The system data 414 also can document theparticular system configurations in use and industrial operationsperformed at each of the industrial automation systems (e.g., 404 ₁, 404₂, 404 _(N)). For example, the system data 414 can document thearrangement of assets, interconnections between devices, the productbeing manufactured at a given facility, an industrial process performedby the assets, a category of industry of each industrial system (e.g.,automotive, oil and gas, food and drug, marine, textiles, etc.), orother relevant information. Among other functions, this data can beaccessed by technical support personnel during a support session so thatparticulars of the customer's unique system and device configurationscan be obtained without reliance on the customer to possess completeknowledge of their assets.

As an example, a given industrial facility can include a packaging line(e.g., the system), which in turn can comprise a number of individualassets (e.g., a filler, a labeler, a capper, a palletizer, etc.). Eachasset can comprise a number of devices (e.g., controllers, variablefrequency drives, HMIs, etc.). Using an architecture similar to thatdepicted in FIG. 2, the training system 402 can collect industrial datafrom the individual devices during operation and can classify the datain the customer data store 406 according to the aforementionedclassifications. Note that some data may be duplicated across more thanone class. For example, a process variable classified under process data410 also can be relevant to the asset-level view of the systemrepresented by the asset data 412. Accordingly, such process variablescan be classified under both classes. Moreover, subsets of data in oneclassification can be derived, determined, or inferred based on dataunder another classification. For example, subsets of system data 414that characterize certain system behaviors can be derived, determined,or inferred based on a long-term analysis of data in the lower-levelclassifications.

In addition to maintaining the data classes (e.g., 408, 410, 412, 414),each customer data store also can maintain a customer model 416 that cancontain data specific to a given industrial entity or customer. Thecustomer model 416 can contain customer-specific information andpreferences, which can be leveraged by (e.g., used by) the trainingsystem 402 to facilitate analyzing the data, determining preferred useractions in connection with performing work tasks associated with theindustrial automation systems (e.g., 404 ₁, 404 ₂, 404 _(N)),determining an alternate user action(s) that can replace a preferreduser action, generating training presentations or modules, automatinguser actions for automatic performance of such actions by an industrialautomation system, determining enhanced work assignments for users,generating simulation models of the industrial automation systems (e.g.,404 ₁, 404 ₂, 404 _(N)), and/or performing other operations by thetraining system 402. Example information that can be maintained in thecustomer model 416 can include a client identifier, client preferencesor requirements with regard to production or work orders associated withan industrial automation system, client contact information specifyingwhich plant personnel are to be notified in response to results of anevaluation of user actions associated with an industrial automationsystem, notification preferences that can specify how plant personnelare to be notified (e.g., email, mobile phone, text message, etc.),service contracts that are active between the customer and the technicalsupport entity, and other such information. The training system 402 canmarry (e.g., associate, unite, map, etc.) data collected for eachcustomer with the corresponding customer model 416 for identificationand event handling purposes.

As noted above, industrial data can be migrated (e.g., communicated)from industrial devices to the cloud platform (e.g., 202) using cloudgateways (e.g., 206 ₁, 206 _(N)). To this end, some devices can includeintegrated cloud gateways that can directly interface each device to thecloud platform. Additionally or alternatively, some configurations canutilize a cloud proxy device that can collect industrial data frommultiple devices associated with the industrial automation systems(e.g., 404 ₁, 404 ₂, 404 _(N)) and can send (e.g., transmit) the data tothe cloud platform. Such a cloud proxy can comprise a dedicated datacollection device, such as a proxy server that can share a network(e.g., communication network) with the industrial devices. Additionallyor alternatively, the cloud proxy can be a peer industrial device thatcan collect data from other industrial devices.

FIGS. 6 and 7 depict block diagrams of example systems 600 and 700,respectively, illustrating respective techniques that can facilitatemigrating industrial data to the cloud platform via proxy devices forclassification and analysis by the training system, in accordance withvarious aspects and implementations of the disclosed subject matter.FIG. 6 depicts the system 600 that can be configured to comprise anindustrial device that can act or operate as a cloud proxy for otherindustrial devices of an industrial automation system. The industrialautomation system can comprise a plurality of industrial devices,including industrial device₁ 606 ₁, industrial device₂ 606 ₂, industrialdevice₃ 606 ₃, and/or (up through) industrial device_(N) 606 _(N), thatcollectively can monitor and/or control one or more controlled processes602. The industrial devices 606 ₁, 606 ₂, 606 ₃, and/or (up through) 606_(N) respectively can generate and/or collect process data relating tocontrol of the controlled process(es) 602. For industrial controllerssuch as PLCs or other automation controllers, this can includecollecting data from telemetry devices connected to an industrialcontroller's I/O, generating data internally based on measured processvalues, etc.

In the configuration depicted in FIG. 6, industrial device₁ 606 ₁ canact, operate, or function as a proxy for industrial devices 606 ₂, 606₃, and/or (up through) 606 _(N), whereby the data 614 from devices 606₂, 606 ₃, and/or (up through) 606 _(N) can be sent (e.g., transmitted)to the cloud via proxy industrial device₁ 606 ₁. Industrial devices 606₂, 606 ₃, and/or (up through) 606 _(N) can deliver their respective data614 to the proxy industrial device₁ 606 ₁ over the plant network orbackplane 612 (e.g., a Common Industrial Protocol (CIP) network or othersuitable network protocol). Using such a configuration, it is onlynecessary to interface one industrial device to the cloud platform (viacloud gateway 608). In some embodiments, the cloud gateway 608 canperform preprocessing on the gathered data prior to migrating the datato the cloud platform (e.g., time stamping, filtering, formatting,normalizing, summarizing, compressing, etc.). The collected andprocessed data can be pushed (e.g., transmitted) to the cloud platformas cloud data 604 via cloud gateway 608. Once migrated to the cloudplatform, the cloud-based training system can classify the dataaccording to the example classifications described herein and/or canutilize the data to facilitate performing various operations relating totraining users to perform work tasks associated with industrialautomation systems more efficiently or safely, automating user actionsto have such actions automatically performed by an industrial automationsystem, determining enhanced or optimized work assignments for users, orperforming other desired tasks or operations.

While the proxy device illustrated in FIG. 6 is depicted as anindustrial device that itself can perform monitoring and/or control of aportion of controlled process(es) 602, other types of devices also canbe configured to serve as cloud proxies for multiple industrial devicesaccording to one or more implementations of the disclosed subjectmatter. For example, FIG. 7 illustrates an example system 700 that cancomprise a firewall box 712 that can serve as a cloud proxy for a set ofindustrial devices 706 ₁, 706 ₂, and/or (up through) 706 _(N). Thefirewall box 712 can act as a network infrastructure device that canallow the plant network 716 to access an outside network such as theInternet, while also providing firewall protection that can preventunauthorized access to the plant network 716 from the Internet. Inaddition to these firewall functions, the firewall box 712 can include acloud gateway 708 that can interface the firewall box 712 with one ormore cloud-based services (e.g., training-related services,automation-related services, data collection services, data storageservices, etc.). In a similar manner to the proxy industrial device 606₁ of FIG. 6, the firewall box 712 of FIG. 7 can collect industrial data714 from including industrial device₁ 706 ₁, industrial device₂ 706 ₂,and/or (up through) industrial device_(N) 706 _(N), which can monitorand control respective portions of controlled process(es) 702. Firewallbox 712 can include a cloud gateway 708 that can apply appropriatepre-processing to the gathered industrial data 714 prior to pushing(e.g., communicating) the data to the cloud-based training system ascloud data 704. Firewall box 712 can allow industrial devices 706 ₁, 706₂, and/or (up through) 706 _(N) to interact with the cloud platformwithout directly exposing the industrial devices to the Internet.

In some embodiments, the cloud gateway 608 of FIG. 6 or cloud gateway708 of FIG. 7 can tag the collected industrial data (e.g., 614 or 714)with contextual metadata prior to pushing the data as cloud data (e.g.,604 or 704) to the cloud platform. Such contextual metadata can include,for example, a time stamp, a location of the device at the time the datawas generated, or other contextual information. In another example, somecloud-aware devices can comprise smart devices capable of determiningtheir own context within the plant or enterprise environment. Suchdevices can determine their location within a hierarchical plant contextor device topology. Data generated by such devices can adhere to ahierarchical plant model that can define multiple hierarchical levels ofan industrial enterprise (e.g., a workcell level, a line level, an arealevel, a site level, an enterprise level, etc.), such that the data canbe identified (e.g., by the training system) in terms of thesehierarchical levels. This can allow a common terminology to be usedacross an entire industrial enterprise to identify devices and theirassociated data. Cloud-based applications and services that model anenterprise according to such an organizational hierarchy can representindustrial controllers, devices, machines, or processes as datastructures (e.g., type instances) within this organizational hierarchyto provide context for data generated by respective devices within theenterprise relative to the enterprise as a whole. Such a convention canreplace the flat name structure that is employed by some industrialapplications.

In some embodiments, the cloud gateway 608 of FIG. 6 or cloud gateway708 of FIG. 7 can comprise uni-directional “data only” gateways that canbe configured only to move data from the premises (e.g., industrialfacility) to the cloud platform. Alternatively, the cloud gateways 608and 708 can comprise bi-directional “data and configuration” gatewaysthat additionally can be configured to receive configuration orinstruction data from services running on the cloud platform. Some cloudgateways can utilize store-and-forward technology that can allow thegathered industrial data (e.g., 614 or 714) to be temporarily storedlocally on storage associated with the cloud gateway (e.g., 608 or 708)in the event that communication between a gateway and the cloud platformis disrupted. In such events, the cloud gateway (e.g., 608 or 708) canforward (e.g., communicate) the stored data to the cloud platform whenthe communication link is re-established.

To ensure a rich and descriptive set of data for analysis purposes, thecloud-based training system can collect device data in accordance withone or more standardized device models. To this end, a standardizeddevice model can be developed for each industrial device. Device modelscan profile the device data that is available to be collected andmaintained by the training system.

FIG. 8 illustrates a block diagram of an example device model 800according to various aspects and implementations of the disclosedsubject matter. In the illustrated example model 800, the device model806 can be associated with a cloud-aware industrial device 802 (e.g., aprogrammable logic controller, a variable frequency drive, an HMI, avision camera, a barcode marking system, etc.). As a cloud-aware device,the industrial device 802 can be configured to automatically detect andcommunicate with the cloud platform 808 upon installation at a plantfacility, simplifying integration with existing cloud-based datastorage, analysis, and applications (e.g., as performed by the trainingsystem described herein). When added to an existing industrialautomation system, the industrial device 802 can communicate with thecloud platform and can send identification and configuration informationin the form of the device model 806 to the cloud platform 808. Thedevice model 806 can be received by the training system 810, which canupdate the customer's device data 812 based on the device model 806. Inthis way, the training system 810 can leverage the device model 806 tofacilitate integrating the new industrial device 802 into the greatersystem as a whole. This integration can include the training system 810updating cloud-based applications or services to recognize the newindustrial device 802, adding the new industrial device 802 to adynamically updated data model of the customer's industrial enterpriseor plant, modifying a sequence of preferred user actions or alternateuser actions for performing a work task in connection with an industrialautomation system, modifying a training presentation or module,modifying a component, process, technique, or algorithm that automatedan action that had been a preferred user action, modifying a workassignment of a user, modifying a simulation model of the industrialautomation system to integrate, incorporate, or include a simulation oran emulation of the new industrial device 802 based on theidentification and configuration information (or other data),determining or predicting a response of the modified industrialautomation system based on a modified simulation model that integratesthe new industrial device 802, making other devices on the plant flooraware of the new industrial device 802, or other desired integration orupdating functions. Once deployed, some data items comprising the devicemodel 806 can be collected and monitored by the training system 810 on areal-time or near real-time basis.

The device model 806 can comprise such information as a deviceidentifier (e.g., model and serial number) associated with theindustrial device 802, status information for the industrial device 802,a currently installed firmware version associated with the industrialdevice 802, device setup data associated with the industrial device 802,warranty specifications associated with the industrial device 802,calculated and/or anticipated KPIs associated with the industrial device802 (e.g., mean time between failures), health and diagnosticinformation associated with the industrial device 802, devicedocumentation, or other such parameters.

In addition to maintaining individual customer-specific data stores foreach industrial enterprise, the training system (e.g., cloud-basedtraining system) also can feed (e.g., transmit) sets of customer data toa global data storage (referred to herein as cloud-based data store orBig Data for Manufacturing (BDFM) data store) for collective big dataanalysis in the cloud platform (e.g., by the training system). FIG. 9presents a block diagram of an example system 900 that can facilitatecollection of data from devices and assets associated with respectiveindustrial automation systems for storage in cloud-based data storage,in accordance with various aspects and implementations of the disclosedsubject matter. As illustrated in FIG. 9, the collection component 310of the training system (e.g., as facilitated by the interface component312) can collect data from devices and assets comprising respectivedifferent industrial automation systems, such as industrial automationsystem₁ 906 ₁, industrial automation system₂ 906 ₂, and/or (up through)industrial automation system_(N) 906 _(N), for storage in a cloud-basedBDFM data store 902. In some embodiments, data maintained in the BDFMdata store 902 can be collected anonymously with the consent of therespective customers. For example, customers can enter into a serviceagreement with a technical support entity whereby the customer can agreeto have their device and asset data collected by the training system inexchange for training-related or other services or a credit towardstraining-related or other services. The data maintained in the BDFM datastore 902 can include all or portions of the classifiedcustomer-specific data described in connection with FIG. 4, as well asadditional data (e.g., derived, determined, or inferred data). Theperformance enhancement component 318 or another component of thetraining system can organize the collected data stored in the BDFM datastore 902 according to device type, system type, application type,applicable industry, or other relevant categories. The performanceenhancement component 318 can analyze data stored in the resultingmulti-industry, multi-customer data store (e.g., BDFM data store 902) tofacilitate learning, determining, or identifying industry-specific,device-specific, and/or application-specific trends, patterns,thresholds (e.g., device-related thresholds, network-related thresholds,etc.), industrial-automation-system interrelationships between devicesor assets, etc., associated with the industrial automation systemsassociated with the cloud platform. In general, the performanceenhancement component 318 can perform a data analysis (e.g., big dataanalysis) on data (e.g., the multi-industrial enterprise data)maintained (e.g., stored in) the BDFM data store 902 to facilitatelearning, determining, identifying, characterizing, simulating, and/oremulating operational industrial-automation-system interrelationships,thresholds, trends, or patterns associated with industrial automationsystems as a function of industry type, application type, equipment inuse, asset configurations, device configuration settings, or other typesof variables.

For example, it can be known that a given industrial asset (e.g., adevice, a configuration of device, a machine, etc.) can be used acrossdifferent industries for different types of industrial applications.Accordingly, the performance enhancement component 318 can identify asubset of the global data stored in BDFM data store 902 relating to theasset or asset type, and perform analysis on this subset of data todetermine how the asset or asset type performs over time and undervarious types of operating conditions for each of multiple differentindustries or types of industrial applications. The performanceenhancement component 318 also can determine the operational behavior ofthe asset or asset type over time and under various types of operatingconditions for each of different sets of operating constraints orparameters (e.g. different ranges of operating temperatures orpressures, different recipe ingredients or ingredient types, etc.). Theperformance enhancement component 318 can leverage (e.g., use) a largeamount of historical data relating to the asset or asset type that hasbeen gathered (e.g., collected and/or aggregated) from many differentindustrial automation systems to facilitate learning or determiningcommon operating characteristics of many diverse configurations ofindustrial assets or asset types at a relatively high degree ofgranularity and under many different operating contexts. The performanceenhancement component 318 can use the learned or determined operatingcharacteristics relating to the industrial assets or asset types tofacilitate performing training-related or other services in connectionwith an industrial automation system.

FIG. 10 illustrates a block diagram of a cloud-based system 1000 thatcan employ a training system to facilitate performing training-relatedand other services associated with industrial automation systems, inaccordance with various aspects and embodiments of the disclosed subjectmatter. As disclosed herein, the training system 1002 can collect,maintain, and monitor customer-specific data (e.g. device data 408,process data 410, asset data 412, and system data 414) relating to oneor more industrial assets 1004 of an industrial enterprise. The trainingsystem 1002 also can collect, maintain, and monitor other data, such asuser-related or user-specific data of users (e.g., operators, managers,technicians, etc.) associated with an industrial enterprise. Inaddition, the training system 1002 can collect and organize industrialdata anonymously (with customer consent) from multiple industrialenterprises, and can store such industrial data in a BDFM data store1006 for collective analysis by the training system 1002, for example,as described herein.

The training system 1002 also can collect product resource informationand maintain (e.g., store) the product resource information in thecloud-based product resource data store 1008. In general, the productresource data store 1008 can maintain up-to-date information relating tospecific industrial devices or other vendor products in connection withindustrial automation systems. Product data stored in the productresource data store 1008 can be administered by the training system 1002and/or one or more product vendors or OEMs. Exemplary device-specificdata maintained by the product resource data store 1008 can includeproduct serial numbers, most recent firmware revisions, preferred deviceconfiguration settings and/or software for a given type of industrialapplication, or other such vendor-provided information.

The system 1000 depicted in FIG. 10 can provide training-related orother services to subscribing customers (e.g., owners of industrialassets 1004). For example, customers can enter an agreement with aproduct vendor or technical support entity to allow their system data tobe gathered anonymously and fed into (e.g., communicated to and storedin) the BDFM data store 1006, and this thereby can expand the store ofglobal data available for collective analysis by the training system1002. In exchange, the vendor or technical support entity can agree toprovide customized training-related or other services to the customer(e.g., services for real-time or near real-time system monitoring,services that can facilitate training users to work more efficiently,services for determining preferred user actions or alternate useractions, services for automating user actions, services for enhancingwork assignments of users, services for generating a simulation of anindustrial automation system, etc.). Alternatively, the customer cansubscribe to one or more available training-related or other servicesthat can be provided by the training system 1002, and optionally canallow their system data to be maintained in the BDFM data store 1006. Insome embodiments, a customer can be given an option to subscribe totraining-related or other services without permitting their data to bestored in the BDFM data store 1006 for collective analysis with datafrom other systems (e.g., industrial automation systems). In such cases,the customer's data will only be maintained as customer data (e.g., incustomer data store 406) for the purposes of performing training-relatedor other services relating to that particular customer, and thecollected customer data will be analyzed in connection with data storedin the BDFM data store 1006 and the product resource data store 1008without that customer data being migrated for storage in the BDFM datastore 1006 for long-term storage and analysis. In another exemplaryagreement, customers can be offered a discount on training-related orother services in exchange for allowing their system data to beanonymously migrated to the BDFM data store 1006 for collective analysisby the training system 1002.

In accordance with various aspects, the customer-specific data caninclude device and/or asset level faults and alarms, process variablevalues (e.g., temperatures, pressures, product counts, cycle times,etc.), calculated or anticipated key performance indicators for thecustomer's various assets, indicators of system behavior over time, andother such information. The customer-specific data also can includedocumentation of firmware versions, configuration settings, and softwarein use on respective devices of the customer's industrial assets.Moreover, the training system 1002 can take into consideration customerinformation encoded in customer model 416, which can have a bearing oninferences made by the training system 1002 based on the analysis (e.g.,big data analysis) stored in the BDFM data store 1006. For example,customer model 416 may indicate a type of industry that is the focus ofthe customer's business (e.g., automotive, food and drug, oil and gas,fibers and textiles, power generation, marine, etc.). Knowledge of thecustomer's industry can facilitate enabling the training system 1002 tocorrelate the customer-specific data with data relating to similarsystems and applications in the same industry, as documented by the datastored in the BDFM data store 1006.

Taken together, customer-specific data and a customer model (e.g., 416)can facilitate accurately modeling the customer's industrial enterpriseat a highly granular level, from high-level system behavior over timedown to the device and software level. The analyzing (e.g., by thetraining system 1002) of this customer-specific data in view of globalindustry-specific and application-specific trends learned via analysisof data stored in the BDFM data storage 1006, as well as vendor-provideddevice information maintained in the product resource data store 1008,can facilitate performing training-related or other services inconnection with industrial automation systems.

In some implementations, the system 1000 (e.g., via the collectioncomponent or training system 1002) also can receive, collect, or captureextrinsic data 1010 from one or more sources (e.g., external datasources). The training system 1002 can use or leverage the extrinsicdata 1010 received, collected, or captured from sources external to acustomer's industrial enterprise, wherein the extrinsic data 1010 canhave relevance to operation of the customer's industrial automationsystem(s). Example extrinsic data 1010 can include, for example, energycost data, material cost and availability data, transportation scheduleinformation from companies that provide product transportation servicesfor the customer, market indicator data, web site traffic statistics,information relating to known information security breaches or threats,or other information relevant to the operation of the customer'sindustrial automation system(s). The training system 1002 can retrieveextrinsic data 1010 from substantially any data source, such as, e.g.,servers or other data storage devices linked to the Internet,cloud-based storage that maintains extrinsic data of interest, or othersources. The training system 1002 can analyze the extrinsic data 1010and/or other data (e.g., user-related data associated with users (e.g.,operators, managers, technicians, other workers) associated with theindustrial automation system(s), device data 408, process data 410,asset data 412, system data 414, etc.) to facilitate performingtraining-related or other services in connection with the industrialautomation system(s).

The aforementioned systems and/or devices have been described withrespect to interaction between several components. It should beappreciated that such systems and components can include thosecomponents or sub-components specified therein, some of the specifiedcomponents or sub-components, and/or additional components.Sub-components could also be implemented as components communicativelycoupled to other components rather than included within parentcomponents. Further yet, one or more components and/or sub-componentsmay be combined into a single component providing aggregatefunctionality. The components may also interact with one or more othercomponents not specifically described herein for the sake of brevity,but known by those of skill in the art.

FIGS. 11-15 illustrate various methods in accordance with one or moreembodiments of the subject application. While, for purposes ofsimplicity of explanation, the one or more methods shown herein areshown and described as a series of acts, it is to be understood andappreciated that the disclosed subject matter is not limited by theorder of acts, as some acts may, in accordance therewith, occur in adifferent order and/or concurrently with other acts from that shown anddescribed herein. For example, those skilled in the art will understandand appreciate that a method could alternatively be represented as aseries of interrelated states or events, such as in a state diagram.Moreover, not all illustrated acts may be required to implement a methodin accordance with the disclosed subject matter. Furthermore,interaction diagram(s) may represent methods, in accordance with thesubject disclosure when disparate entities enact disparate portions ofthe methods. Further yet, two or more of the disclosed example methodscan be implemented in combination with each other, to accomplish one ormore features or advantages described herein.

FIG. 11 illustrates a flow diagram of an example method 1100 that canfacilitate training users associated with an industrial automationsystem associated with an industrial enterprise based on cloud-baseddata relating to the industrial enterprise, in accordance with variousimplementations and embodiments of the disclosed subject matter. Themethod 1100 can be implemented by a training system that can comprise aperformance enhancement component and/or another component(s) (e.g., acollection component (e.g., a cloud-based collection component), a datastore (e.g., a cloud-based data store), etc.).

At 1102, a set of data relating to an industrial automation system canbe analyzed to facilitate performing one or more functions or operationsrelating to enhancing performance of a user associated with theindustrial automation system or enhancing performance of the industrialautomation system, wherein the set of data is maintained in acloud-based platform (e.g., comprising the cloud-based data store). Theperformance enhancement component can analyze the set of data relatingto the industrial automation system. The set of data can comprise dataassociated with the industrial automation system and/or one or moreother industrial automation systems that can comprise an industrialdevice(s), industrial process(es), or industrial asset(s) that can bethe same as or similar to an industrial device(s), industrialprocess(es), or industrial asset(s) associated with the industrialautomation system. The set of data also can comprise data relating toone or more users (e.g., operators, managers, technicians, etc.) thatare associated with the industrial automation system and the one or moreother industrial automation systems.

The set of data can be data that is stored in a cloud-based data store,wherein the set of data or at least a subset of the data can be received(e.g., collected, obtained, detected, etc.) from the industrialautomation system and stored in the cloud-based data store. The set ofdata can comprise, for example, device-related data (e.g., industrialdevice-related data), asset-related data, process-related data (e.g.,industrial-automation-process-related data), user-related data,customer-related data, and/or other data associated with an industrialenterprise. The user-related data can comprise, for example, datarelating to the interactions or behavior of users in connection with theindustrial automation system and the performance or response of theindustrial automation system in response to the interactions or behaviorof the users in connection with the industrial automation system, asmore fully disclosed herein. The data can be migrated (e.g.,communicated) to the cloud platform using one or more cloud gateways(e.g., communication gateway components) that can serve asuni-directional or bi-directional communication interfaces betweenindustrial devices of the industrial automation system and the cloudplatform. The device-related data, asset-related data, process-relateddata, user-related data, customer-related data, and/or otherindustrial-automation-system-related data can be stored in thecloud-based data store in association with identification information,such as, for example, a user identifier or other user-specificinformation, or a customer identifier or other customer-specificinformation. For example, for a subset of data relating to an industrialprocess on which a user (e.g., operator) is working, the process-relateddata (e.g., data relating to the performance of the industrial process)and/or user-related data (e.g., data relating to the interactions orbehavior of the user in connection with working on the industrialprocess) can respectively comprise a user identifier or otheruser-specific information associated with the user to facilitateassociating (e.g., tagging, linking, etc.) the process-related dataand/or user-related data with the user, so that the process-related dataand/or user-related data can be identified (e.g., by the performanceenhancement component or other component) as being associated with theuser.

The collection component can facilitate collecting or obtaining the setof data, and can store the set of data in the cloud-based data store.The performance enhancement component can access the cloud-based datastore and can receive (e.g., retrieve, obtain, etc.) the set of datafrom the cloud-based data store. The performance enhancement componentcan analyze the set of data to facilitate performing one or morefunctions or operations relating to enhancing performance of a user(s)associated with the industrial automation system or performance of theindustrial automation system. For example, the performance enhancementcomponent can analyze the set of data to facilitate determining oridentifying a correlation between a user action(s) (e.g., a user actionor sequence of user actions) and a performance of the industrialautomation system determined to be favorable, in accordance with the setof defined performance criteria, wherein information relating to suchcorrelation can be used to facilitate enhancing performance of a user(s)associated with the industrial automation system or performance of theindustrial automation system.

At 1104, a correlation between a user action(s) of a user associatedwith the industrial automation system and performance of the industrialautomation system that is determined to be favorable can be determinedor identified based at least in part on the results of the analysis ofthe set of data, in accordance with the set of defined performancecriteria. The performance enhancement component can determine oridentify the correlation between the user action(s) of the userassociated with the industrial automation system and performance of theindustrial automation system that is determined (e.g., by theperformance enhancement component) to be favorable based at least inpart on the results of the analysis of the set of data, in accordancewith the set of defined performance criteria. For instance, theperformance enhancement component can determine or identify one or moreinstances of the industrial automation system, or a portion (e.g., anindustrial process, a subset of industrial devices, etc.) thereof,performing favorably (e.g., performing at least up to a definedthreshold level of performance), based at least in part on the dataanalysis results, in accordance with the set of defined performancecriteria. The performance enhancement component also can determine oridentify one or more user actions that at least were partiallyresponsible for achieving the one or more instances of favorableperformance of the industrial automation system, or a portion thereof,based at least in part on the data analysis results, wherein theindustrial-automation-system-related data and/or user-related data ofthe set of data can be associated with a user identifier or otheruser-specific information that is associated with the user to facilitateidentifying or determining that the user's interactions or behavior withrespect to the industrial automation system was at least partiallyresponsible for the favorable performance of the industrial automationsystem, or portion thereof.

As desired, the performance enhancement component also can identify ordetermine other instances of less favorable or relatively poorperformance of the industrial automation system, or portion thereof, byother users (or the user at other times), based at least in part on thedata analysis results, in accordance with the set of defined performancecriteria, wherein such less favorable or relatively poor performance ofthe industrial automation system, or portion thereof, can be associatedwith user interactions or behaviors with respect to the industrialautomation system that are different than the interactions or behaviorsof the user that had resulted in the favorable performance of theindustrial automation system, or portion thereof. The performanceenhancement component can compare the user interactions and behaviors ofthe user that are associated with the favorable performance of theindustrial automation system, or portion thereof, with the differentuser interactions and behaviors of other users (or the user at othertimes) that are associated with less favorable or relatively poorperformance of the industrial automation system, or portion thereof.Such a comparison by the performance enhancement component canfacilitate enabling the performance enhancement component to determinewhich user interactions or behaviors of the user with respect to theindustrial automation system, or portion thereof, were at leastpartially responsible for the favorable performance of the industrialautomation system, or portion thereof. This can facilitate enabling theperformance enhancement component to determine or identify thecorrelation between the user action(s) of the user with respect to theindustrial automation system and favorable performance of the industrialautomation system.

In some implementations, based at least in part on the determined oridentified correlation between the user action(s) of the user and thedetermined favorable performance of the industrial automation system,the performance enhancement component can facilitate determiningtraining-related or other functions or operations (e.g., determiningpreferred user actions in relation to the industrial automation system,determining poor or unsafe user practices in relation to the industrialautomation system, training users to perform their tasks moreefficiently with respect to the industrial automation system (e.g.,based at least in part on the preferred user actions), automatingpreferred user actions, etc.) that can facilitate training users orautomating preferred user actions in connection with the industrialautomation system.

FIG. 12 depicts a flow diagram of an example method 1200 that canfacilitate training users associated with an industrial automationsystem associated with an industrial enterprise based on cloud-baseddata relating to the industrial enterprise, in accordance with variousimplementations and embodiments of the disclosed subject matter. Themethod 1200 can be implemented by a training system that can comprise aperformance enhancement component and/or another component(s) (e.g., acloud-based collection component, a cloud-based data store, etc.).

At 1202, a set of data relating to a set of industrial automationsystems comprising one or more industrial automation systems can becaptured and/or collected. The training system can comprise a collectioncomponent that can capture and/or collect the set of data relating tothe set of industrial automation systems. The set of data can comprisedata relating to industrial devices, industrial assets, industrialprocesses, and network devices, associated with the one or moreindustrial automation systems of the set of industrial automationsystems. The set of data also can include user-related data orcustomer-related data. For example, the user-related data can comprisedata relating to the interactions or behaviors of respective users(e.g., operators, managers, technicians, etc.) who perform respectivetasks in connection with an industrial automation system(s), andperformance results of the industrial automation system(s) in responseto the performing of the respective user actions (e.g., comprising theinteractions or behaviors) by the respective users. The set ofindustrial automation systems can be associated with one or moreindustrial enterprises.

In some implementations, all or part of the training system can belocated in a cloud platform. For example, the performance enhancementcomponent, the collection component, the data store, and/or anothercomponent(s) of the training system can be located in the cloudplatform. In other implementations, certain components (e.g.,performance enhancement component or collection component) can belocated outside of the cloud platform and can access the cloud platform(e.g., the data store in the cloud platform) to facilitate analyzing thedata in the data store to facilitate performing functions, operations,or tasks relating to training users associated with industrialautomation systems, automating desired (e.g., preferred) actions thathave been performed by a user(s), or performing other functions,operations, or tasks. One or more sensor components (e.g., video sensorcomponent, audio sensor component, motion sensor component, locationsensor component, etc.) can be distributed throughout the industrialautomation system environment to facilitate sensing, detecting, and/orcapturing information relating to user interactions or behaviors ofusers performing work tasks with respect to respective portions of theindustrial automation system, information relating to operations,performance, or responses of the respective portions of the industrialautomation system in connection with (e.g., in response to) the userinteractions or behaviors of the users performing the work tasks withrespect to the respective portions of the industrial automation system,or other information relating to the users or the industrial automationsystem.

At 1204, the set of data can be stored in a data store. The collectioncomponent can facilitate storing the set of data in the data store.

At 1206, the set of data can be analyzed. The performance enhancementcomponent can access the cloud-based data store and can retrieve,obtain, or read the set of data from the cloud-based data store. Theperformance enhancement component can analyze the set of data (e.g.,perform big data analysis on the set of data) to facilitate determiningor identifying a preferred user action(s) of a user with respect to theindustrial automation system, or a portion (e.g., industrial process,subset of industrial devices, etc.) thereof.

At 1208, a preferred user action(s) of the user with respect to theindustrial automation system can be determined based at least in part onthe results of the analysis of the set of data. The performanceenhancement component can analyze the set of data to facilitatedetermining or identifying one or more actions or behavior of the userin connection with the user performing work tasks on the industrialautomation system, or a portion thereof, that resulted in favorableperformance of the industrial automation system, or portion thereof(e.g., resulted in performance of the industrial automation system, orportion thereof, that satisfied a defined threshold performanceparameter or parameter range), in accordance with the set of definedperformance criteria. The performance enhancement component also canfacilitate determining or identifying the one or more actions orbehavior of the user as resulting in favorable performance of theindustrial automation system based at least in part on a comparison ofthe relative performance of the industrial automation system resultingfrom the user's actions or behavior with the performance (e.g.,relatively poorer performance) of the industrial automation systemresulting from another user's (users') actions or behavior(s).

In some implementations, the performance enhancement component also canfacilitate modifying a preferred user action(s) to facilitate achievingan even more favorable performance by or response from the industrialautomation system, in accordance with the set of defined performancecriteria. For instance, the preferred user action(s) can comprise a setof user actions, and the performance enhancement component can analyzethe respective user actions in the set of user actions to determinewhether any of those user actions can be improved further to furtherimprove the favorable performance of the industrial automation system.For example, the set of user actions may comprise four user actions,wherein the performance enhancement component can determine that threeof the user actions are at least substantially optimal as they are,while the remaining user action in the set is substantially less thanoptimal and can be improved by modifying that remaining user action. Theperformance enhancement component can determine a modification that canbe implemented to modify that remaining user action, and the preferreduser action(s) can be modified based at least in part on themodification.

At 1210, a training presentation can be generated based at least in parton the preferred user action(s). The performance enhancement componentcan generate a training presentation that can comprise informationrelating to the preferred user action(s). The training presentation canbe used to facilitate training other users (e.g., inexperienced orpoorer performing users) to perform better and/or more efficiently whenperforming the work tasks associated with the preferred user action(s)while working with the industrial automation system. The trainingpresentation can be or comprise, for example, a video (e.g., an animatedvideo, a video of a user performing or discussing performance of a worktask), a visual illustration, an audio presentation, printed materials(e.g., written instructions), a poster, and/or a placard, presenting orillustrating the preferred user action(s).

In some implementations, the performance enhancement component also candetermine or identify poor or unsafe user practices of users in relationto the industrial automation system (e.g., user actions that result inless favorable or poor performance of the industrial automation systemor are unsafe), based at least in part on the data analysis results, inaccordance with the set of defined performance criteria. For instance,the performance enhancement component can determine or identify actionsor behaviors of users in connection with an operation(s) or events)associated with the industrial automation system that result in arelatively poor performance or response by the industrial automationsystem, are at least potentially unsafe as potentially being harmful toa user(s) or to the industrial automation system, and/or that haveresulted in harm to a user(s) or the industrial automation system, inaccordance with the set of defined performance criteria.

The performance enhancement component can generate a trainingpresentation (e.g., the same training presentation that comprises apreferred user action(s), or a separate training presentation) that canillustrate or present the poor or unsafe user action(s) and/orcomprising a set of instructions that can facilitate training users tonot perform the poor or unsafe user action(s) in connection with theoperation(s) or events) associated with the industrial automation systemand/or training users to perform the relevant work tasks by performingthe preferred user action(s). The performance enhancement component canstore the training presentation(s), or a portion thereof, in thecloud-based data store, and/or can provide the training presentation(s)for use (e.g., presentation) in training users.

In some implementations, after the operation at reference numeral 1208is performed, the method 1200 can proceed to reference point A. In someimplementations, the method 1300, as depicted in FIG. 13, can proceedfrom reference point A, wherein the preferred user action(s) can be used(e.g., analyzed) to facilitate automating the preferred user action(s),as more fully disclosed herein. In other implementations, the method1400, as depicted in FIG. 14, can proceed from reference point A,wherein an alternate user action(s), which can be performed in place ofa preferred user action(s), can be determined, as more fully disclosedherein.

FIG. 13 presents a flow diagram of an example method 1300 that canfacilitate automating one or more preferred user actions in connectionwith a work task associated with an industrial automation system, inaccordance with various aspects and embodiments of the disclosed subjectmatter. The method 1300 can be implemented by a training system that cancomprise a performance enhancement component and/or another component(s)(e.g., a cloud-based collection component, a cloud-based data store,etc.). In some implementations, the method 1300 can proceed fromreference point A of method 1200, wherein a preferred user action(s) hasbeen determined or identified in connection with a work task associatedwith an industrial automation system.

At 1302, data relating to the one or more preferred user actionsrelating to a work task associated with the industrial automation systemcan be analyzed. The performance enhancement component can analyze datarelating to the one or more preferred user actions to facilitatedetermining or designing a component(s) (e.g., industrial component),device(s) (e.g., industrial device), process(es) (e.g., industrialprocess), technique(s), and/or algorithm(s), etc., that can perform(e.g., automatically or dynamically perform) the one or more preferred(user) actions in connection with the work task that had been performedby the user.

At 1304, one or more components, devices, processes, techniques, and/oralgorithms, etc., can be determined or designed based at least in parton the results of the analysis of the data relating to the one or morepreferred user actions. The performance enhancement component candetermine or design the one or more components, devices, processes,techniques, and/or algorithms, etc., based at least in part on theanalysis results. In some implementations, the performance enhancementcomponent can emulate or simulate the one or more preferred useractions, emulate or simulate the one or more components, devices,processes, techniques, and/or algorithms, etc., and/or emulate orsimulate the industrial automation system, based at least in part on theanalysis results. The performance enhancement component can generate asimulation(s) of the operation of the industrial automation system(e.g., as modified to incorporate the emulated or simulated one or morepreferred user actions, emulate or simulate the one or more components,devices, processes, techniques, and/or algorithms, etc.) to facilitatedetermining or designing the one or more preferred user actions, emulateor simulate the one or more components, devices, processes, techniques,and/or algorithms, etc., verifying that the one or more preferred useractions, emulate or simulate the one or more components, devices,processes, techniques, and/or algorithms, etc., will satisfactorilyperform or operate to achieve a favorable performance of the industrialautomation system that is sufficiently or substantially comparable tothe favorable performance of the industrial automation system that wasachieved through the performance of the one or more preferred useractions, and/or evaluating the performance of the simulation of the oneor more components, devices, processes, techniques, and/or algorithms,etc.

At 1306, the one or more components, devices, processes, techniques,and/or algorithms, etc., can be generated based at least in part on thedetermination or design of the one or more components, devices,processes, techniques, and/or algorithms, etc. The performanceenhancement component or another component(s) can generate the one ormore components, devices, processes, techniques, and/or algorithms,etc., based at least in part on the determination or design of the oneor more components, devices, processes, techniques, and/or algorithms,etc.

At 1308, the industrial automation system can be modified to incorporateor integrate the one or more components, devices, processes, techniques,and/or algorithms, etc. The performance enhancement component or anothercomponent(s) can modify the industrial automation system to incorporateor integrate the one or more components, devices, processes, techniques,and/or algorithms, etc. The industrial automation system, as modified,can perform (e.g., automatically or dynamically perform) the one or morepreferred (formerly user) actions in connection with the associated worktask for the industrial automation system, rather than having the useror another user perform the one or more preferred user actions. Asdesired, the performance enhancement component can store informationrelating to the automating of the one or more preferred user actions inthe data store.

FIG. 14 illustrates a flow diagram of another example method 1400 thatcan facilitate determining one or more alternate user actions that auser can perform to complete a work task(s) to achieve a same orsubstantially same performance result as when the work task(s) iscompleted by a user (e.g., another user) by performing one or more useractions (e.g., preferred user actions), in accordance with variousaspects and embodiments of the disclosed subject matter. In someinstances, a first user is able to perform one or more user actions(e.g., preferred user actions) to complete a work task in connectionwith the industrial automation system that produces a favorableperformance or response by the industrial automation system, where,unfortunately, a second user may not be able to perform the one or moreuser actions that the first user was able to perform when trying tocomplete the work task. For example, the second user may have physicallimitations or other limitations that can make it difficult, if notimpossible, for the second user to perform the one or more user actionsthe way the first user was able to perform them. The method 1400 can beemployed to determine one or more alternate user actions that can beperformed by the second user to complete a work task(s) to achieve asame or substantially same performance result as when the work task(s)is completed by the first user through performing one or more useractions (e.g., preferred user actions).

The method 1400 can be implemented by a training system that cancomprise a performance enhancement component and/or another component(s)(e.g., a collection component, a cloud-based data store, etc.). In someimplementations, the method 1400 can proceed from reference point A ofmethod 1200, wherein a preferred user action(s) has been determined oridentified in connection with a work task associated with an industrialautomation system.

At 1402, data relating to the one or more preferred user actionsrelating to the work task(s) associated with the industrial automationsystem can be analyzed. The performance enhancement component cananalyze data relating to the one or more preferred user actions tofacilitate determining one or more alternate user actions that anotheruser can perform to complete the work task(s), or a substantiallysimilar work task(s), to facilitate obtaining the same or substantiallythe same performance results by the industrial automation system as theperformance results derived from the performing of one or more preferreduser actions to complete the work task in connection with operation ofthe industrial automation system. The performance enhancement component

At 1404, physical elements, mental elements, and/or other elementsinvolved in the performance of the one or more preferred user actions tocomplete the work task(s) can be determined based at least in part onthe analysis results. The performance enhancement component candetermine or identify the physical elements, mental elements, and/orother elements involved in the performance of the one or more preferreduser actions by the user to complete the work task(s) can be determinedbased at least in part on the analysis results. The physical elementscan comprise or can relate to, for example, physical movements, physicalspeed of the movements, physical accuracy of the movements, etc., of theuser with respect to the performance of the one or more preferred useractions. The mental elements can comprise or can relate to, for example,a type of action the user has taken in response to a condition of theindustrial automation system, a reaction time of the user to thecondition, etc. The performance enhancement component can determine orderive the mental elements from the actions taken by the user withrespect to performing the one or more preferred user actions.

At 1406, the physical skills, work skills, intelligence, and/or otherfactors of the second user can be determined. The performanceenhancement component can determine the physical skills, work skills,intelligence, and/or other factors (e.g., work-related and/orperformance-related characteristics) of the second user based at leastin part on data analysis results relating to the physical skills, workskills, intelligence, and/or other factors of the second user.

At 1408, differences between the physical elements, mental elements,and/or other elements involved in the performance of the one or morepreferred user actions to complete the work task(s) and the physicalskills, work skills, intelligence, and/or other factors of the seconduser can be determined, based at least in part on the results of thedata analysis. The performance enhancement component can compare orevaluate the physical elements, mental elements, and/or other elementsinvolved in the performance of the one or more preferred user actions tocomplete the work task(s) in relation to the physical skills, workskills, intelligence, and/or other factors of the second user. This canfacilitate enabling the performance enhancement component to determinealternate user actions that the second user can have the ability toperform to achieve the same or substantially the same performanceresults by the industrial automation system as the performance resultsderived from the performing of one or more preferred user actions tocomplete the work task.

At 1410, one or more alternate user actions, which can be performed tocomplete the work task(s) in place of a preferred user action(s) of theone or more preferred user actions, can be determined based at least inpart on the differences between the physical elements, mental elements,and/or other elements involved in the performance of the one or morepreferred user actions to complete the work task(s) and the physicalskills, work skills, intelligence, and/or other factors of the seconduser. The performance enhancement component can determine the one ormore alternate user actions, which can be performed by the second user(or another user) in place of a preferred user action(s) of the one ormore preferred user actions, to facilitate completing the work task(s)to achieve the same or substantially same result in a different way(e.g., to achieve the same or substantially same favorable performanceas can be achieved by performing the one or more preferred useractions). For example, the preferred user actions may comprise four useractions, wherein the performance enhancement component can determinethat the second user is able to perform three of the user actions in amanner that is the same or substantially the same as the first user, butdue to physical limitations of the second user, the second user is notable to perform the fourth preferred user action in the way that thefirst user was able to perform it. The performance enhancement componentcan determine one or more alternate user actions that the second usercan perform (e.g., can be physically capable of performing) in place ofthe fourth preferred user action, wherein performing the one or morealternate user actions can achieve the same or substantially the sameresult as performing the fourth preferred user action. Employing themethod 1400, the performance enhancement component can determinedifferent types of alternate user actions with regard to a work task fordifferent users based at least in part on the respective physicalskills, work skills, intelligence, and/or other factors of the differentusers.

At 1412, a training presentation, comprising information relating to theone or more alternate user actions, can be generated. The trainingpresentation can be or comprise, for example, a video (e.g., an animatedvideo), a visual illustration, an audio presentation, printed materials(e.g., written instructions), and/or a placard, presenting orillustrating the one or more alternate user actions and/or one or moreof the preferred user actions (e.g., the sequence of alternate useractions and/or preferred user actions that the second user is able toperform to complete the work task(s)). The training presentation can beused to facilitate training the second user and/or another user(s) toperform the work task(s) associated with the industrial automationsystem.

FIG. 15 presents a flow diagram of an example method 1500 that canfacilitate desirably (e.g., acceptably, optimally, etc.) determiningrespective assignments for respective users who perform work tasks inconnection with an industrial automation system, in accordance withvarious aspects and embodiments of the disclosed subject matter. Themethod 1500 can be implemented by a training system that can comprise aperformance enhancement component and/or another component(s) (e.g., acloud-based collection component, a cloud-based data store, etc.).

At 1502, a set of data relating to a set of industrial automationsystems comprising one or more industrial automation systems can becaptured and/or collected. The training system can comprise a collectioncomponent that can capture and/or collect the set of data relating tothe set of industrial automation systems. The set of data can comprisedata relating to industrial devices, industrial assets, industrialprocesses, and network devices, associated with the one or moreindustrial automation systems of the set of industrial automationsystems. The set of data also can include user-related data orcustomer-related data. For example, the user-related data can comprisedata relating to the interactions or behaviors of respective users(e.g., operators, managers, technicians, etc.) in connection with anindustrial automation system(s) as those respective users perform theirrespective work tasks. The set of industrial automation systems can beassociated with one or more industrial enterprises. The training systemcan comprise other features or functions, such as those features orfunctions disclosed herein.

At 1504, the set of data can be stored, for example, in a cloud-baseddata store. The collection component can facilitate storing the set ofdata in the data store.

At 1506, the set of data can be analyzed. The performance enhancementcomponent can access the cloud-based data store and can retrieve,obtain, or read the set of data from the cloud-based data store. Theperformance enhancement component can analyze the set of data (e.g.,perform big data analysis on the set of data) to facilitate desirably(e.g., acceptably, optimally, etc.) determining or identifyingrespective work assignments for respective users who perform work tasksin connection with an industrial automation system.

At 1508, desirable (e.g., most acceptable, optimal) respective workassignments for the respective users, in connection with working withthe industrial automation system, can be determined based at least inpart on the results of the data analysis, in accordance with the set ofdefined performance criteria. For example, in connection with operationof the industrial automation system, the work assignments can comprise afirst work assignment associated with performing a first set of tasks inrelation to a first portion (e.g., industrial process, subset ofindustrial devices, etc.) of the industrial automation system and asecond work assignment associated with performing a second set of tasksin relation to a second portion of the industrial automation system,wherein a first user and a second user each can be at least minimallyqualified to perform the first work assignment or the second workassignment. The performance enhancement component can analyze the set ofdata and can determine that the set of data indicates that theperformance or response of industrial automation system will be morefavorable if the first user is assigned to perform the first workassignment and the second user is assigned to perform the second workassignment as compared to the performance or response of the industrialautomation system if the first user is assigned to perform the secondwork assignment and the second user is assigned to perform the firstwork assignment. Based at least in part on this analysis result, theperformance enhancement component can determine that the first user isto be assigned, or at least is recommended by the performanceenhancement component to be assigned, to perform the first workassignment and the second user is to be assigned, or at least isrecommended by the performance enhancement component to be assigned, toperform the second work assignment.

The performance enhancement component can provide (e.g., present,transmit, print, etc.) the desirable (e.g., most acceptable, optimal)respective work assignments for the respective users, in connection withworking with the industrial automation system, as an output (e.g., via adisplay screen, a message, a printout, etc.).

Embodiments, systems, and components described herein, as well asindustrial control systems and industrial automation environments inwhich various aspects set forth in the subject specification can becarried out, can include computer or network components such as servers,clients, programmable logic controllers (PLCs), automation controllers,communications modules, mobile computers, wireless components, controlcomponents and so forth which are capable of interacting across anetwork. Computers and servers include one or more processors—electronicintegrated circuits that perform logic operations employing electricsignals—configured to execute instructions stored in media such asrandom access memory (RAM), read only memory (ROM), a hard drives, aswell as removable memory devices, which can include memory sticks,memory cards, flash drives, external hard drives, and so on.

Similarly, the term PLC or automation controller as used herein caninclude functionality that can be shared across multiple components,systems, and/or networks. As an example, one or more PLCs or automationcontrollers can communicate and cooperate with various network devicesacross the network. This can include substantially any type of control,communications module, computer, Input/Output (I/O) device, sensor,actuator, and human machine interface (HMI) that communicate via thenetwork, which includes control, automation, and/or public networks. ThePLC or automation controller can also communicate to and control variousother devices such as I/O modules including analog, digital,programmed/intelligent I/O modules, other programmable controllers,communications modules, sensors, actuators, output devices, and thelike.

The network can include public networks such as the internet, intranets,and automation networks such as control and information protocol (CIP)networks including DeviceNet, ControlNet, and Ethernet/IP. Othernetworks include Ethernet, DH/DH+, Remote I/O, Fieldbus, Modbus,Profibus, CAN, wireless networks, serial protocols, and so forth. Inaddition, the network devices can include various possibilities(hardware and/or software components). These include components such asswitches with virtual local area network (VLAN) capability, LANs, WANs,proxies, gateways, routers, firewalls, virtual private network (VPN)devices, servers, clients, computers, configuration tools, monitoringtools, and/or other devices.

In order to provide a context for the various aspects of the disclosedsubject matter, FIGS. 16 and 17 as well as the following discussion areintended to provide a brief, general description of a suitableenvironment in which the various aspects of the disclosed subject mattercan be implemented.

With reference to FIG. 16, an example environment 1600 for implementingvarious aspects of the aforementioned subject matter includes a computer1612. The computer 1612 includes a processing unit 1614, a system memory1616, and a system bus 1618. The system bus 1618 couples systemcomponents including, but not limited to, the system memory 1616 to theprocessing unit 1614. The processing unit 1614 can be any of variousavailable processors. Multi-core microprocessors and othermultiprocessor architectures also can be employed as the processing unit1614.

The system bus 1618 can be any of several types of bus structure(s)including the memory bus or memory controller, a peripheral bus orexternal bus, and/or a local bus using any variety of available busarchitectures including, but not limited to, 8-bit bus, IndustrialStandard Architecture (ISA), Micro-Channel Architecture (MSA), ExtendedISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB),Peripheral Component Interconnect (PCI), Universal Serial Bus (USB),Advanced Graphics Port (AGP), Personal Computer Memory CardInternational Association bus (PCMCIA), and Small Computer SystemsInterface (SCSI).

The system memory 1616 includes volatile memory 1620 and nonvolatilememory 1622. The basic input/output system (BIOS), containing the basicroutines to transfer information between elements within the computer1612, such as during start-up, is stored in nonvolatile memory 1622. Byway of illustration, and not limitation, nonvolatile memory 1622 caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable PROM (EEPROM), or flashmemory. Volatile memory 1620 includes random access memory (RAM), whichacts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as synchronous RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), anddirect Rambus RAM (DRRAM).

Computer 1612 also includes removable/non-removable,volatile/non-volatile computer storage media. FIG. 16 illustrates, forexample a disk storage 1624. Disk storage 1624 includes, but is notlimited to, devices like a magnetic disk drive, floppy disk drive, tapedrive, Jaz drive, Zip drive, LS-100 drive, flash memory card, or memorystick. In addition, disk storage 1624 can include storage mediaseparately or in combination with other storage media including, but notlimited to, an optical disk drive such as a compact disk ROM device(CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RWDrive) or a digital versatile disk ROM drive (DVD-ROM). To facilitateconnection of the disk storage 1624 to the system bus 1618, a removableor non-removable interface is typically used such as interface 1626.

It is to be appreciated that FIG. 16 describes software that acts as anintermediary between users and the basic computer resources described insuitable operating environment 1600. Such software includes an operatingsystem 1628. Operating system 1628, which can be stored on disk storage1624, acts to control and allocate resources of the computer 1612.System applications 1630 take advantage of the management of resourcesby operating system 1628 through program modules 1632 and program data1634 stored either in system memory 1616 or on disk storage 1624. It isto be appreciated that one or more embodiments of the subject disclosurecan be implemented with various operating systems or combinations ofoperating systems.

A user enters commands or information into the computer 1612 throughinput device(s) 1636. Input devices 1636 include, but are not limitedto, a pointing device such as a mouse, trackball, stylus, touch pad,keyboard, microphone, joystick, game pad, satellite dish, scanner, TVtuner card, digital camera, digital video camera, web camera, and thelike. These and other input devices connect to the processing unit 1614through the system bus 1618 via interface port(s) 1638. Interfaceport(s) 1638 include, for example, a serial port, a parallel port, agame port, and a universal serial bus (USB). Output device(s) 1640 usesome of the same type of ports as input device(s) 1636. Thus, forexample, a USB port may be used to provide input to computer 1612, andto output information from computer 1612 to an output device 1640.Output adapters 1642 are provided to illustrate that there are someoutput devices 1640 like monitors, speakers, and printers, among otheroutput devices 1640, which require special adapters. The output adapters1642 include, by way of illustration and not limitation, video and soundcards that provide a means of connection between the output device 1640and the system bus 1618. It should be noted that other devices and/orsystems of devices provide both input and output capabilities such asremote computer(s) 1644.

Computer 1612 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1644. The remote computer(s) 1644 can be a personal computer, a server,a router, a network PC, a workstation, a microprocessor based appliance,a peer device or other common network node and the like, and typicallyincludes many or all of the elements described relative to computer1612. For purposes of brevity, only a memory storage device 1646 isillustrated with remote computer(s) 1644. Remote computer(s) 1644 islogically connected to computer 1612 through a network interface 1648and then physically connected via communication connection 1650. Networkinterface 1648 encompasses communication networks such as local-areanetworks (LAN) and wide-area networks (WAN). LAN technologies includeFiber Distributed Data Interface (FDDI), Copper Distributed DataInterface (CDDI), Ethernet/IEEE 802.3, Token Ring/IEEE 802.5 and thelike. WAN technologies include, but are not limited to, point-to-pointlinks, circuit switching networks like Integrated Services DigitalNetworks (ISDN) and variations thereon, packet switching networks, andDigital Subscriber Lines (DSL).

Communication connection(s) 1650 refers to the hardware/softwareemployed to connect the network interface 1648 to the system bus 1618.While communication connection 1650 is shown for illustrative clarityinside computer 1612, it can also be external to computer 1612. Thehardware/software necessary for connection to the network interface 1648includes, for exemplary purposes only, internal and externaltechnologies such as, modems including regular telephone grade modems,cable modems and DSL modems, ISDN adapters, and Ethernet cards.

FIG. 17 is a schematic block diagram of a sample computing and/ornetworking environment 1700 with which the disclosed subject matter caninteract. The computing and/or networking environment 1700 can includeone or more clients 1702. The client(s) 1702 can be hardware and/orsoftware (e.g., threads, processes, computing devices). The computingand/or networking environment 1700 also can include one or more servers1704. The server(s) 1704 can also be hardware and/or software (e.g.,threads, processes, computing devices). The servers 1704 can housethreads to perform transformations by employing one or more embodimentsas described herein, for example. One possible communication between aclient 1702 and servers 1704 can be in the form of a data packet adaptedto be transmitted between two or more computer processes. The computingand/or networking environment 1700 can include a communication framework1706 that can be employed to facilitate communications between theclient(s) 1702 and the server(s) 1704. The client(s) 1702 are operablyconnected to one or more client data stores 1708 that can be employed tostore information local to the client(s) 1702. Similarly, the server(s)1704 are operably connected to one or more server data stores 1710 thatcan be employed to store information local to the servers 1704.

What has been described above includes examples of the disclosed subjectmatter. It is, of course, not possible to describe every conceivablecombination of components or methods for purposes of describing thedisclosed subject matter, but one of ordinary skill in the art mayrecognize that many further combinations and permutations of thedisclosed subject matter are possible. Accordingly, the disclosedsubject matter is intended to embrace all such alterations,modifications, and variations that fall within the spirit and scope ofthe appended claims.

In particular and in regard to the various functions performed by theabove described components, devices, circuits, systems and the like, theterms (including a reference to a “means”) used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (e.g., a functional equivalent), even though not structurallyequivalent to the disclosed structure, which performs the function inthe herein illustrated exemplary aspects of the disclosed subjectmatter. In this regard, it will also be recognized that the disclosedsubject matter includes a system as well as a computer-readable mediumhaving computer-executable instructions for performing the acts and/orevents of the various methods of the disclosed subject matter.

In addition, while a particular feature of the disclosed subject mattermay have been disclosed with respect to only one of severalimplementations, such feature may be combined with one or more otherfeatures of the other implementations as may be desired and advantageousfor any given or particular application. Furthermore, to the extent thatthe terms “includes,” and “including” and variants thereof are used ineither the detailed description or the claims, these terms are intendedto be inclusive in a manner similar to the term “comprising.”

In this application, the word “exemplary” is used to mean serving as anexample, instance, or illustration. Any aspect or design describedherein as “exemplary” is not necessarily to be construed as preferred oradvantageous over other aspects or designs. Rather, use of the wordexemplary is intended to present concepts in a concrete fashion.

Various aspects or features described herein may be implemented as amethod, apparatus, or article of manufacture using standard programmingand/or engineering techniques. The term “article of manufacture” as usedherein is intended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. For example, computerreadable media can include but are not limited to magnetic storagedevices (e.g., hard disk, floppy disk, magnetic strips . . . ), opticaldisks [e.g., compact disk (CD), digital versatile disk (DVD) . . . ],smart cards, and flash memory devices (e.g., card, stick, key drive . .. ).

What is claimed is:
 1. A system, comprising: a memory that storescomputer-executable components; a processor, operatively coupled to thememory, that executes computer-executable components, thecomputer-executable components comprising: a collection componentconfigured to collect a set of data associated with a set of devices ofan industrial automation system and a set of users associated with theindustrial automation system, and store the set of data in a data storethat is part of a cloud platform; and a performance enhancementcomponent configured to determine a correlation between a set of useractions of a user in connection with performance of a work taskassociated with operation of the industrial automation system and adefined favorable performance of the industrial automation system, basedon a result of an analysis of the set of data.
 2. The system of claim 1,wherein the performance enhancement component is further configured todetermine the set of user actions of the user is a set of definedpreferred user actions based on the result of the analysis of the datathat indicates the set of user actions satisfies a defined thresholdperformance parameter associated with the defined favorable performance.3. The system of claim 2, wherein the performance enhancement componentis further configured to generate a training presentation based on theset of defined preferred user actions to facilitate training one or moreusers of the set of users, wherein the user is in the set of users. 4.The system of claim 3, wherein the training presentation comprises atleast one of a video, an animated video, a visual illustration, an audiopresentation, a training model, an interactive training simulation,printed materials, written instructions, a training manual, a trainingguide, a searchable training or troubleshooting database, a poster, or aplacard, that presents information relating to the set of definedpreferred user actions.
 5. The system of claim 2, wherein theperformance enhancement component is further configured to determine analternate user action for a second user of the set of users to performto facilitate performance of the work task in place of a definedpreferred user action of the set of defined preferred users actions tofacilitate training the second user to perform the work task to satisfya defined threshold acceptable performance level even though it isdetermined that the second user is not able to perform the definedpreferred user action.
 6. The system of claim 5, wherein the performanceenhancement component is further configured to determine the alternateuser action based on a set of results of the analysis of the set ofdata, wherein the set of data comprises data relating to awork-performance-related characteristic associated with the second userand a performance-related characteristic relating to the definedpreferred user action.
 7. The system of claim 5, wherein the performanceenhancement component is further configured to determine the alternateuser action that the performance enhancement component determines willproduce or substantially produce the defined favorable performance ofthe industrial automation system.
 8. The system of claim 2, wherein theperformance enhancement component is further configured to determine ordesign at least one of a device, a process, a technique, or an algorithmthat emulates at least one defined preferred user action of the set ofdefined preferred user actions, based on the result of the analysis ofthe data, to facilitate automation of the at least one defined preferreduser action for performance of the at least one defined preferred useraction by a portion of the industrial automation system comprising atleast one of the device, the process, the technique, or the algorithm.9. The system of claim 8, wherein the performance enhancement componentis further configured to facilitate incorporation or integration of atleast one of the device, the process, the technique, or the algorithminto or with the industrial automation system.
 10. The system of claim1, wherein the performance enhancement component is further configuredto determine a second set of user actions performed by a second user inconnection with performance of the work task associated with theoperation of the industrial automation system is associated with adefined unfavorable performance of the industrial automation system,based on a second result of the analysis of the data that indicates thesecond set of user actions at least one of satisfies a defined safetythreshold that indicates the second set of user actions is unsafe ordoes not satisfy a defined threshold performance parameter associatedwith the defined favorable performance.
 11. The system of claim 10,wherein the performance enhancement component is further configured todetermine one or more modified user actions that are determined to beable to replace one or more user actions of the second set of useractions to facilitate the performance of the work task to achieve aperformance result of the industrial automation system that is at leastmore favorable than the defined unfavorable performance of theindustrial automation system associated with the second set of useractions.
 12. The system of claim 10, wherein the performance enhancementcomponent is further configured to at least one of generate a trainingpresentation based on the one or more modified user actions or generatea recommendation message to recommend that the one or more modified useractions be performed in place of the one or more user actions, tofacilitate training the second user.
 13. The system of claim 1, whereinthe performance enhancement component is further configured to determinean enhanced set of work assignments comprising a first work assignmentthat is assigned to the user to perform a first set of work tasks inconnection with the operation of the industrial automation system and asecond work assignment that is assigned to a second user to perform asecond set of work tasks in connection with the operation of theindustrial automation system based on a set of results of the analysisof the set of data, wherein the set of data comprises a subset of datarelating to a first set of work-performance-related characteristicsassociated with the user and a second set of work-performance-relatedcharacteristics associated with the second user.
 14. The system of claim13, wherein the performance enhancement component is further configuredto determine the enhanced set of work assignments based on adetermination that performance of the industrial automation system willbe higher in response to assignment of the first work assignment to theuser and assignment of the second work assignment to the second userthan performance of the industrial automation system in response toassignment of the first work assignment to the second user andassignment of the second work assignment to the user.
 15. The system ofclaim 1, wherein at least one of the collection component or theperformance enhancement component is part of the cloud platform.
 16. Thesystem of claim 15, further comprising an interface component configuredto interface the cloud platform with the industrial automation systemvia a cloud gateway device of the industrial automation system tofacilitate communication of the set of data from the industrialautomation system to at least one of the collection component or theperformance enhancement component.
 17. The system of claim 16, whereinat least one of the performance enhancement component, the collectioncomponent, or the interface component facilitates capture of the set ofdata associated with the set of devices and the set of users, and thecommunication of the set of data to at least one of the collectioncomponent or the performance enhancement component.
 18. The system ofclaim 1, further comprising: a set of sensor components associated withat least one of the set of users or the industrial automation system,wherein the set of sensor components are configured to sense conditionsassociated with at least one of the set of users or the industrialautomation system and generate a subset of the set of data based on theconditions associated with at least one of the set of users or theindustrial automation system.
 19. The system of claim 1, wherein the setof data comprises at least one of data relating to the set of users,data associated with a communication device associated with the user,data relating to at least one customer entity associated with theindustrial automation system, data relating to an industrial device ofthe set of devices, data relating to an industrial process associatedwith the set of devices, data relating to an industrial asset associatedwith the industrial automation system, data relating to anetwork-related device of the set of devices that facilitates datacommunications associated with the industrial automation system, datarelating to an operating system associated with the industrialautomation system, data relating to software associated with theindustrial automation system, or data relating to firmware associatedwith the industrial automation system.
 20. A method, comprising:obtaining a set of data associated with a set of devices of anindustrial automation system and a set of users associated with theindustrial automation system for storage in a data store of a cloudplatform associated with the industrial automation system; anddetermining a correlation between a set of user actions of a user inconnection with performing a work duty associated with operation of theindustrial automation system and a defined favorable performance resultof the industrial automation system, based on a result of analysis ofthe set of data.
 21. The method of claim 20, further comprising:determining that the set of user actions of the user satisfies a definedthreshold performance parameter associated with the defined favorableperformance of the industrial automation system based on the result ofthe analysis of the data; and determining the set of user actions of theuser is a set of defined preferred user actions in response todetermining that the set of user actions of the user satisfies thedefined threshold performance parameter.
 22. The method of claim 21,further comprising: generating a training presentation based on the setof defined preferred user actions to facilitate training one or moreusers of the set of users, wherein the user is in the set of users. 23.The method of claim 21, further comprising: determining that a seconduser of the set of users is not capable of performing a definedpreferred user action of the set of defined preferred users actions inconnection with the work duty based on a set of results of the analysisof the set of data, wherein the set of data comprises data relating to awork-performance-related characteristic associated with the second userand a performance-related characteristic relating to the definedpreferred user action; and in response to determining that the seconduser is not capable of performing the defined preferred user action,determining an alternate user action for the second user to perform tofacilitate performing the work duty in place of the defined preferreduser action to facilitate training the second user to perform the workduty to satisfy a defined threshold acceptable performance level eventhough it is determined that the second user is not able to perform thedefined preferred user action.
 24. The method of claim 23, wherein thedetermining the alternate user action comprises determining an alternateuser action that results or substantially results in obtaining thedefined favorable performance of the industrial automation system. 25.The method of claim 21, further comprising: determining at least one ofa device, a process, a technique, or an algorithm that emulates at leastone defined preferred user action of the set of defined preferred useractions, based on the result of the analysis of the data, to facilitateautomation of the at least one defined preferred user action forperforming of the at least one defined preferred user action by aportion of the industrial automation system that comprises at least oneof the device, the process, the technique, or the algorithm.
 26. Themethod of claim 25, further comprising: facilitating integrating atleast one of the device, the process, the technique, or the algorithmwith the industrial automation system
 27. The method of claim 20,further comprising: determining a second set of user actions performedby a second user in connection with performing the work duty associatedwith the operation of the industrial automation system is associatedwith a defined unfavorable performance of the industrial automationsystem, based on a second result of the analysis of the data thatindicates the second set of user actions at least one of satisfies adefined safety threshold that indicates the second set of user actionsis unsafe or does not satisfy a defined threshold performance parameterassociated with the defined favorable performance.
 28. The method ofclaim 27, further comprising: determining one or more modified useractions that are determined to be able to replace one or more useractions of the second set of user actions to facilitate the performingof the work duty to achieve a performance result of the industrialautomation system that is at least more favorable than the definedunfavorable performance of the industrial automation system associatedwith the second set of user actions.
 29. The method of claim 28, furthercomprising: at least one of: generating a training presentation based onthe one or more modified user actions to facilitate training the seconduser, or generating a recommendation message to recommend that the oneor more modified user actions be performed in place of the one or moreuser actions to facilitate training the second user.
 30. The method ofclaim 20, further comprising: determining an enhanced set of workassignments comprising a first work assignment that is assigned to theuser to perform a first set of work tasks in connection with theoperation of the industrial automation system and a second workassignment that is assigned to a second user to perform a second set ofwork tasks in connection with the operation of the industrial automationsystem based on a set of results of the analysis of the set of data,wherein the set of data comprises a subset of data relating to a firstset of work-performance-related characteristics associated with the userand a second set of work-performance-related characteristics associatedwith the second user.
 31. The method of claim 30, further comprising:determining that performance of the industrial automation system will behigher in response to assignment of the first work assignment to theuser and assignment of the second work assignment to the second userthan performance of the industrial automation system in response toassignment of the first work assignment to the second user andassignment of the second work assignment to the user, wherein thedetermining the enhanced set of work assignments further comprisesdetermining the enhanced set of work assignments in response todetermining that the performance of the industrial automation systemwill be higher in response to assignment of the first work assignment tothe user and assignment of the second work assignment to the seconduser.
 32. The method of claim 20, further comprising: interfacing thecloud platform with the industrial automation system; and monitoring theindustrial automation system via the interfacing of the cloud platformwith the industrial automation system to facilitate the obtaining of theset of data.
 33. The method of claim 20, further comprising: capturingthe set of data associated with the set of devices and the set of users;and storing the set of data in the data store of the cloud platform. 34.The method of claim 20, further comprising: detecting conditionsassociated with at least one of the set of users or the industrialautomation system; and generating a subset of the set of data based onthe conditions associated with at least one of the set of users or theindustrial automation system.
 35. A computer-readable storage mediumstoring computer-executable instructions that, in response to execution,cause a system comprising a processor to perform operations, comprising:collecting a set of data associated with a set of devices of anindustrial automation system and a set of users associated with theindustrial automation system for storage in a data store of a cloudplatform associated with the industrial automation system; anddetermining a correlation between a set of user actions of a user inconnection with performing a work task associated with operation of theindustrial automation system and a defined favorable performance resultof the industrial automation system, based on a result of analysis ofthe set of data.
 36. The computer-readable medium of claim 35, whereinthe operations further comprise: generating a training presentationbased on the correlation between the set of user actions of the user inconnection with performing the work task associated with operation ofthe industrial automation system and the defined favorable performanceresult of the industrial automation system; and presenting the trainingpresentation to facilitate training one or more users of the set ofusers, wherein the user is in the set of users.